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Full text of "Effects of capital regulation and information asymmetries on bank lending"

EFFECTS OF CAPITAL REGULATION AND INFORMATION 
ASYMMETRIES ON BANK LENDING 



By 
DAVID FREDERIC MARCUS 



A DISSERTATION PRESENTED TO THE GRADUATE 

SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL 

FULFILLMENT OF THE REQUIREMENTS FOR THE 

DEGREE OF DOCTOR OF PHILOSOPHY 

UNIVERSITY OF FLORIDA 

1996 



UNIVERSITY OF FLORIDA LIBRARIES 



... .,*►., ,».»«. 



ACKNOWLEDGMENTS 

I owe special thanks to Professors Chris James, Joel Houston, Mike Ryngaert, and Mark 
Flannery for their excellent guidance and many patient discussions. I have also benefited 
greatly from conversations with Professors Jon Hamilton, Carolyn Takeda, Charles 
Hadlock, and Jon Garfinkel. Most of all, I owe an enormous debt to my family, and 
especially my wife Deborah, for their dedication to helping me realize my goal. 



TABLE OF CONTENTS 

page 

ACKNOWLEDGMENTS ii 

ABSTRACT iv 

CHAPTERS 

1 INTRODUCTION 1 

2 BACKGROUND DISCUSSION 8 

Literature on Capital Regulation and Bank Growth 8 

Internal Additions to Capital and Bank Holding Companies 1 5 

3 DATA 22 

4 BANK HOLDING COMPANY ANALYSIS 27 

5 BANK SUBSIDIARY ANALYSIS 44 

6 EXTERNAL CAPITAL ISSUANCE 57 

7 SUMMARY AND CONCLUSIONS 78 

APPENDIX ESTIMATION OF RISK-WEIGHTED ASSETS 80 

REFERENCES 84 

BIOGRAPHICAL SKETCH 87 



in 



Abstract of Dissertation Presented to the Graduate School of the University of Florida in 
Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy 

EFFECTS OF CAPITAL REGULATION AND INFORMATION ASYMMETRIES ON 

BANK LENDING 

By 

David Frederic Marcus 

August 1996 

Chairman: Christopher M. James 

Major Department: Finance, Insurance, and Real Estate 

This paper provides evidence that asymmetric information problems increase the 

costs of external finance for banking firms. Specifically, I find a positive and significant 

relation between bank loan growth and internally generated additions to capital. 

Consistent with the hypothesis that capital requirements limit bank financing choices, this 

cash flow sensitivity of investment is positively related to the extent that capital 

requirements are binding. I also find that the formulation of the capital ratio itself is 

important in determining bank loan growth. Specifically, with regulators enforcing 

leverage-based capital standards, banks can rely on a buffer stock of securities to fund 

investment in a liquidity crisis. However, the use of risk-based standards substantially 

reduces the effectiveness of securities as financial slack. My results also suggest that bank 

holding companies establish internal capital markets to allocate scarce capital among their 

subsidiaries in response to costly external finance. I find that investment by bank 

iv 



subsidiaries is more sensitive to the cash flows and capitalization of its holding company 
than its own cash flows and capitalization. Finally, I find that the severity of information 
asymmetries affects both the likelihood of an external capital issuance and the expected 
costs of issuance. I find a negative relation between the cash flow sensitivity of investment 
and the probability that banks issue external capital. I also find that firms that anticipate 
larger external finance costs exhibit significantly higher cash flow sensitivities of 
investment. 



CHAPTER 1 
INTRODUCTION 

Over the last fifteen years, banks operating in the United States have faced 
increasingly stringent capital requirements. Concurrently, the growth rate of bank lending 
has been sharply declining. Recent empirical work has questioned whether the more rigid 
capital standards induced the slowdown in loan growth. 1 These studies rely on the critical 
assumption that banks face information asymmetries which create a wedge between 
internal and external financing costs. This results in capital market frictions that tie loan 
growth to internally generated funds. 2 Previously, scholars believed that the federal safety 
net covering deposits removed financial firms from this problem. However, capital 
requirements restrict the amount of (insured) debt funds that banks can utilize. As a 
result, banks may benefit from holding capital greater than regulatory requirements 
(surplus capital) as financial slack. This suggests that banks with more surplus capital 
should invest more, and their investment should be less constrained by internally generated 
funds than banks with less surplus capital. Moreover, increases in capital requirements 
can prompt a decline in lending as banks replenish their surplus capital to its (new) optimal 
level. 



1 For an excellent review see Berger and Udell (1994) and Sharpe (1995). 

2 See Fazzari, Hubbard, and Petersen (1988); Hoshi, Kashyap, and Scharfstein 
(1991), and Bernanke, Gertler, and Gilchrist (1994). 

1 



2 
A second effect of capital regulation is that the formulation of regulatory capital 
ratios affects bank liquidity stocks. During the 1980s, regulators relied on leverage-based 
requirements, mandating minimum capital levels per total assets. Under leverage-based 
requirements, banks facing a funding shortage can support new loans through the 
liquidation of other assets, namely securities, without changing required capital levels. In 
this vein, security holdings may substitute for surplus capital by decreasing the dependency 
on internally generated funds. However, beginning in 1 990 regulators adopted risk-based 
standards which require minimum capital per risk-weighted assets. Risk-weighted assets 
are determined by assigning a weight based on credit risk to every bank asset. Since 
securities receive a lower risk weight than loans, asset substitution could substantially 
influence capital adequacy. In particular, an increase in loans increases the amount of 
required bank capital even if securities are liquidated. Therefore, a change from leverage 
to risk based standards may affect loan growth by reducing the role of securities as 
liquidity and effectively increasing banks' desired surplus capital. 

Given the existence of capital market frictions which tie investment to earnings, the 
magnitude of the effect of internally generated funds may proxy for the size of the wedge 
in financing costs. As a result, banks that are more constrained by internally generated 
funds may be more concerned about facing a funding shortage. This suggests that these 
banks may have a larger incentive to hedge their risks and therefore may rely more heavily 
on derivatives and other off-balance sheet assets. Moreover, these banks may be less 
likely to issue external capital and may anticipate larger costs when bringing capital issues 
to the market (either in the form of underwriter fees or abnormal stock returns). 



3 
Most recent studies on capital regulation and loan growth focus on the adoption of 
risk-based requirements and the simultaneous "credit crunch" of the early 1990s (in which 
banks allegedly decreased lending in response to the new capital standards). In general, 
these studies document a positive correlation between loan growth and capitalization. 
Nonetheless, whether the decline in growth results from more stringent capital 
requirements is not obvious. In particular, the observed relationship between loan growth 
and capitalization may arise from either capital market imperfections or simply because 
earnings and capitalization proxy for the profitability of lending opportunities. 

An additional problem with prior studies of the relationship between capital 
regulation and loan growth is that most concentrate on individual bank data. However, 
the majority of banks are subsidiaries of multiple bank holding companies. If holding 
companies manage capital on a consolidated basis, one would expect at best a weak link 
between investment and earnings at the subsidiary level. Moreover, regulators have 
recently attempted to require holding companies to inject capital into undercapitalized 
subsidiaries. 3 This 'source of strength' doctrine mandates that bank holding companies 
must downstream capital to its subsidiary banks if they fail capital standards, as long as 
this act does not cause the holding company itself to fail capital requirements. Thus, it 
follows that the primary determinant of loan growth should be the capitalization and 
earnings of the holding company and not the subsidiary bank. 

In this paper I investigate the relationship between loan growth and internally 
generated funds for a sample of 289 publicly traded bank holding companies from 1982- 



See Keeton (1990), Fallon (1991), and Wall and Petersen (1995) 



1994. Following the approach of Fazzari, Hubbard, and Petersen (1988), I assume that 
capital market imperfections create a wedge between internal and external financing costs. 
As a result, banks prefer to grow with internally generated funds. To control for growth 
opportunities I include a measure of Tobin's Q and the bank's previous loan growth as 
explanatory variables. I test the hypothesis that capital requirements increase banks' costs 
of finance, and therefore I expect a negative relation between the overall sensitivity to 
internally generated funds and surplus capital. In addition, I test the hypothesis that the 
formulation of capital standards affects the role of securities holdings as liquidity. In 
particular, I expect a negative relation between the sensitivity to internally generated funds 
and securities holdings to exist while regulators impose leverage-based standards, but not 
risk-based standards. I also examine the relation between the overall sensitivity to 
internally generated funds and the amount of off-balance sheet assets utilized to test how 
the severity of capital market imperfections affects banks' incentives to hedge risks. 
To further test the existence of capital market frictions, I follow an approach 
similar to Lamont (1993) and examine the relation between loan growth of individual bank 
subsidiaries of multiple bank holding companies and the subsidiary's own earnings, as well 
as the earnings of other subsidiaries within the same holding company. 4 A finding that 
subsidiary banks are more constrained by the earnings of the rest of the holding company 
than its own earnings is consistent with the operation of an internal capital market. Since 
holding company wide earnings may proxy for investment opportunities at the subsidiary 



4 Lamont (1993) examines investment of firms with subsidiaries in both oil and 
non-oil related business. His results suggest that investment of non-oil related subsidiaries 
is positively related to the cash flows of the oil subsidiaries. 



bank, I include both loan growth at other subsidiaries and the earnings of all non-bank 
subsidiaries within the holding company as explanatory variables. As an additional test I 
examine how the severity of information asymmetries at the holding company level affect 
subsidiary bank dependence on both its own and holding company earnings. 

An additional test on the effects of capital market frictions is to examine the 
relation between the severity of information asymmetries and external capital issuances. 
Following Bayless and Chaplinsky (1991, 1996), I develop a model which predicts 
security issuance based on firm and market characteristics. Assuming the overall 
sensitivity to internally generated funds proxies for the severity of capital market frictions, 
banks that are more constrained by internally generated funds are expected to be less likely 
to issue external capital. To control for a potential causality problem, I test this relation 
using a lagged value of the sensitivity to internally generated funds. Because capital 
deficient banks are likely to be the most constrained by internally generated funds and the 
most in need of an external capital issuance, I include a dummy variable for whether banks 
maintain minimum capital ratios as an explanatory variable. 

Continuing along these lines, the costs associated with bringing an external capital 
issue to the market should be related to the degree of information asymmetries. Following 
Calomiris and Himmelberg (1995), I estimate underwriting fees associated with security 
issuance after controlling for selectivity bias and examine the relation between these fees 
and the sensitivity to internally generated funds. In addition, I predict the abnormal stock 
returns associated with the announcement of a security issuance. A finding of a positive 
relation between these costs of external finance and the sensitivity to internally generated 



funds provides additional support for the hypothesis that the reliance on internal funds 
proxies for the severity of capital market frictions. 

Overall, I find a strong positive correlation between bank holding company loan 
growth and internally generated additions to capital after controlling for differences in 
growth opportunities. Consistent with the hypothesis that capital requirements increase 
banks' financing costs, I find that the sensitivity of loan growth to earnings is significantly 
greater among banks that are close to or below the minimum capital requirement. In 
addition, I find that securities holdings provide banks with significant financial slack by 
decreasing the dependency on internally generated funds. Moreover, after the 
implementation of risk-based standards in 1990, loan growth is unrelated to securities 
holdings, suggesting that the type of capital requirement enforced can have a significant 
impact on loan growth. Also, consistent with the hypothesis that the severity of 
information asymmetries influences the incentives to hedge, I find that banks that are more 
constrained by internally generated funds hold more off-balance sheet assets. 

In tests of the relation between loan growth and earnings at the subsidiary level, I 
find that subsidiary loan growth is positively related to both its own earnings and the 
earnings of other bank subsidiaries within the holding company. However, the sensitivity 
of loan growth to the earnings of other subsidiaries is significantly greater than the 
subsidiary's own earnings. Moreover, subsidiary loan growth is unrelated to its own 
capitalization, but positively related to the holding company's capitalization. I also find 
that subsidiary loan growth is negatively related to loan growth at other subsidiaries within 
the holding company. This is consistent with the operation of an internal capital market in 



7 
which the overall investment capacity of the holding company is constrained. In addition, 
I find that subsidiary loan growth is positively related to the earnings of non-bank 
subsidiaries within the holding company. Furthermore, I find that as holding companies 
become more constrained by internally generated funds, subsidiaries grow slower and 
become more dependent on holding company earnings. 

Finally, I examine the relation between the severity of information asymmetries, the 
decision to issue external capital, and costs associated with an external capital issuance. I 
find that the severity of information asymmetries affects banks' decisions to issue external 
capital. In particular, my results document a negative relation between the overall 
sensitivity to internally generated funds and the probability that the firm chooses to issue. 
In tests of the relation between issuance costs and information asymmetries, I find that 
banks that anticipate higher costs of security issuance are more constrained by internally 
generated funds. Specifically, I find that the sensitivity to internally generated funds is 
significantly higher for banks which expect high underwriting fees for issuing external 
funds or large negative abnormal stock returns following the announcement of a security 
issuance. 

The remainder of the paper is organized in six chapters. Chapter 2 provides a 
background discussion on the effects of capital requirements on bank investment activity. 
Chapter 3 describes the data and empirical methodology. Chapter 4 documents empirical 
tests for the holding company sample, while Chapter 5 documents the subsidiary bank 
sample. Chapter 6 presents the external capital issuance analysis, and Chapter 7 
summarizes and concludes. 



CHAPTER 2 
BACKGROUND DISCUSSION 

Literature on Capital Regulation and Bank Growth 



Bank capital regulation has changed substantially over the past fifteen years. 
Before 1981, regulators relied solely on discretion when evaluating a bank's capital 
adequacy. To eliminate potential bias in the examination process, regulators adopted a 
minimum leverage-based capital ratio in 1981. ' A problem with leverage-based standards 
is that the riskiness of bank assets is not considered when determining the minimum capital 
level. Accordingly, banks had incentives to alter the riskiness of their asset portfolios. In 
response, regulators created risk-based standards, which were implemented beginning in 
1990. 2 These new guidelines assign risk weights to all bank assets, including off-balance 
sheet assets, based on credit risk. 3 For example, commercial and industrial loans receive 
100% risk weight, while cash and Treasury securities receive a risk weight of zero. 

Some recent theoretical models have attempted to link capital regulation and bank 
growth. Using an options-pricing model, Furlong and Keeley (1989) investigate how 



1 Regulations required that banks maintain a minimum total capital ratio of 5.5%. 
In 1985, regulators increased the standard to 6%. 

2 Regulators imposed a minimum risk-based ratio of 7.25% beginning in 1990, and 
8% beginning in 1992. 

3 See Bank Holding Company Supervision Manual, section 4060, for a complete 
description of risk-based capital standards. 

8 



9 
increases in requirements affect bank risk taking behavior. Public opinion held that banks 
would respond to increased requirements by increasing asset risk to offset the cost of 
holding more capital. Contrary to this prediction, Furlong and Keeley show that banks 
actually decrease asset risk following an increase in requirements. Although this is 
excellent news for the FDIC, it has less to say about how bank growth responds, if at all, 
to changes in capital requirements. 

Passmore and Sharpe (1994) analyze how economic shocks and regulatory shifts 
affect a profit maximizing bank. One prediction of their model is that increased capital 
requirements cause a slowdown in loan growth by raising the marginal cost of funds. In 
addition, they provide evidence that the resultant decline in bank lending may be most 
pronounced at highly capitalized banks. This occurs because banks hold capital as a buffer 
against regulatory intervention and funding shortages. One reason why banks may choose 
high capital ratios is that they face high costs of capital shortages. Therefore, these firms 
may react more to an increase in required capital ratios. This finding is at odds with the 
popular notion that banks which are close to minimum standards would be the most 
affected by an increase in capital requirements. 4 This work allows for the possibility that 
well capitalized institutions may be affected by increases in capital standards. In 
particular, I test the hypothesis that banks rely on surplus capital (amount above 
regulatory requirements) as a buffer stock against funding shortages. 



4 Berger and Udell (1994) note that the commercial and industrial lending decline 
in the early 1990s was not concentrated in banks with low risk-based capital ratios. In 
turn, they cite this as evidence that risk-based standards were unlikely to have caused the 
credit crunch. 



10 
Thakor (1995) develops an asymmetric information model in which banks perform 
two key lending functions: pre-lending screening and post-lending monitoring. One result 
of his model is that an increase in capital requirements elevates the endogenously 
determined probability of a borrower being credit rationed by the entire banking system, 
thereby reducing aggregate lending. This is consistent with Passmore and Sharpe and 
suggests that the recent increase in capital standards may have significantly contributed to 
the simultaneous decline in loan growth. 

Because securities receive a lower risk-weight than loans, a change from leverage 
to risk-based standards can have a significant impact on bank behavior. First, securities 
require little or no capital backing, which increases their attractive relative to loans. 
Consequently, banks may have gained incentive to shift assets out of loans and into 
securities. Second, the role of securities as liquidity may have been diminished. With 
regulators enforcing leverage-based requirements, banks could rely on a buffer stock of 
securities to fund growth during a liquidity crisis. However, with risk-based standards 
capital ratios decline following this type of asset substitution. Therefore, banks may have 
experienced a drain on liquidity following this change in regulatory regimes. These 
problems led recent empirical studies to investigate whether the regime shift induced the 
"credit crunch" of the early 1990s. To date, the literature offers mixed predictions. 

Peek and Rosengren (1995) and Hancock and Wilcox (1993) examine how loan 
growth differs for banks based on whether they pass or fail capital requirements. Peek and 
Rosengren (1995) study growth of New England banks which underwent formal 
regulatory enforcement actions between 1989 and 1993. After controlling for size, time, 



11 

and region, they find that banks under formal action grow at a significantly slower pace. 
In addition, they find that these banks were growing at a faster pace than other banks in 
the quarters leading up to the enforcement actions. Thus, their evidence is consistent with 
regulatory intervention significantly decreasing loan growth. This suggests that if the 
change to risk-based standards caused an increase in regulatory intervention, then this 
change may have contributed to the credit crunch. 

However, the authors provide no proof of an increase in the number of banks with 
enforcement actions based on the change to risk-based standards. In fact, the large 
number of institutions under formal action may reflect the regional economic difficulties 
during their sample period and not changes in capital regulations. Also, they do not 
include a control period to compare the relationship between enforcement actions and 
growth. Although this does not take away from their insight that in the 1990s regulatory 
intervention has substantial effects (for New England banks), it does limit their ability to 
test whether the change to risk-based standards had any impact on loan growth. 

Hancock and Wilcox (1993) study the cross-sectional determinants of bank loan 
and security growth during 1990 and 1991 based on whether banks experienced a "capital 
shortfall" during their sample period. Capital shortfall is defined as the difference between 
the actual 1990 year end capital and the regulatory minimum based on the 1990 beginning 
of year total assets and a 5% capital requirement. 5 In short, their findings reveal that a 
capital shortfall has a large negative cross-sectional effect on loan growth in 1990. 



The authors reasoned that banks could largely anticipate the amount of capital 
that would be on the books at year end, and that this is the figure that should influence 
growth. 



12 
A potential problem with this study is the authors' treatment of capital shortfall. 
They assume that a 5% minimum leverage-based standard (introduced in 1981) remains in 
effect through 1991. However, capital standards have been increased twice since 1981 6 
Hence, the authors significantly understate the number of banks experiencing a capital 
shortfall, and actually focus on only the most capital deficient banks. Therefore, 
ascertaining exactly how a capital shortfall affects growth is difficult given the formulation 
of these tests. 

Due to the possible incentive banks may have gained to shift assets out of loans 
and into securities, Haubrich and Wachtel (1993) explore how risk-based standards may 
influence asset portfolio choice. The authors sort banks according to risk-based ratios and 
analyze subsequent changes in portfolio mix. Their results suggest that banks in lower 
capital groups tend to shift toward assets with lower risk weights, and in particular away 
from commercial loans and into Treasury securities. They interpret this as evidence that 
risk-based standards may have partially caused the credit crunch. 

Since the authors fail to provide a benchmark period for comparing bank behavior, 
however, it is possible that any changes in portfolio mix observed is simply optimal 
rebalancing without regard to capital requirements. Likewise, the authors do not control 
for bank size, growth opportunities, loan loss provisions, or previous growth, all of which 
may significantly impact asset portfolio shifts. 



' It could be argued that the change to risk-based standards did not constitute an 
increase in requirements since some banks would actually find their required capital 
declining due to the new standards. However, for the majority of banks, and especially the 
larger banks, the change to risk-based standards can be considered an increase in 
requirements. 



13 
Given the existence of capital market imperfections, loan growth may be directly 
related to capitalization. In this vein, Bernanke and Lown (1991) and Berger and Udell 
(1994) investigate a direct link between capitalization and growth. Bernanke and Lown 
(1991) examine growth as a function of beginning of period capital ratios. In their 
interpretation, coefficients on capitalization serve to identify short run effects over a 
period during which capital might be reasonably treated as exogenous. Relying on 
aggregate state level data, their findings suggest that loan growth is positively related to 
capitalization. A potential problem with this study is the utilization of state level data. 
This analysis is likely to drop potentially important information specific to individual 
banks. 

Probably the most cited study in this area, Berger and Udell (1994) use a long 
panel of observations to investigate asset growth's relationship with capitalization. In 
particular, they examine differences in asset expansion during the credit crunch (early 
1990s) relative to earlier years, especially with regard to capitalization. They find that 
loan growth during the credit crunch does not appear to be consistently more sensitive to 
capitalization than it was in the 1980s. In addition, they find that the decline in lending 
was not concentrated in banks with low capital ratios. The authors interpret these findings 
as evidence that risk-based standards were unlikely to have been the culprit behind the 
contraction in lending during the early 1 990s. 

A basic problem in interpreting these results is that no change in coefficient 
estimates does not necessarily imply no impact from increased regulatory standards. 
Specifically, if all banks respond in a similar fashion to the change in regulations, then 



14 
coefficient estimates may not change at all. Therefore, the finding that loan growth is not 
more affected by capitalization during the 1990s is not proof that the change to risk-based 
standards had no effect. Moreover, the finding of a decline in lending at banks with high 
capital ratios does not imply that the change in capital standards had no effect. Recall that 
Passmore and Sharpe (1994) find that reductions in lending may be more severe at banks 
with high capital ratios. 

In this study, I test for the effects of capital regulation on loan growth in two ways. 
First, consistent with prior studies I expect a positive relation between capital and growth. 
More specifically, I hypothesize that banks consider the cushion between their capital and 
required capital as a type of financial slack. Thus, an external shock which depletes this 
slack could induce a slowdown in growth. Second, I test for the effects of the change to 
risk-based standards through the relation between securities holdings and growth. In 
particular, I expect securities to be positively related to growth in the 1980s, but unrelated 
to growth in the 1990s, since risk-based standards may diminish the effectiveness of 
securities as a buffer stock. 

To improve upon previous studies, I provide evidence of an increase in the number 
of capital deficient banks following the change to risk-based standards. I employ a long 
panel of observations to observe bank behavior over time. Moreover, I use a number of 
control variables to alleviate problems associated with bank growth opportunities and size. 
Finally, I calculate surplus capital, which is in the same spirit as Hancock and Wilcox's 
capital shortfall. However, my measure requires banks to comply with capital 
requirements exactly as defined by regulations. 



15 
Internal Additions to Capital and Bank Holding Companies 

It is widely accepted that banks play an important role in mitigating information 
problems. Given this role, assuming that at least some bank assets will be difficult for 
outsiders to value seems logical. Even so, access to federally insured deposits and the 
absence of capital requirements may insulate banks from any adverse selection problems in 
raising external funds. However, limited deposit insurance combined with capital 
requirements suggest that banks must raise at least some funds in markets in which 
asymmetric information may create a wedge between internal and external financing 
costs. 7 This implies that the more constrained banks are by capital requirements, the more 
sensitive their growth might be to internally generated additions to capital (earnings 
available to augment regulatory capital). 8 

A number of studies (some cited above) examine the empirical relation between 
bank growth and capitalization, and in particular investigate the sensitivity of growth to 
capital shocks. However, except work by Baer and McElravey (1993), studies do not 
explicitly examine the sensitivity of loan growth to internal additions to capital. Since an 
underlying assumption for capital shocks to adversely affect loan growth is capital market 
friction which creates a wedge between internal and external finance costs, loan growth is 
expected to be positively related to internal additions to capital. 



7 See Myers and Majluf (1984), and Fazzari, Hubbard, and Petersen (1988). 

Due to the way in which capital requirements are calculated, internal additions to 
capital differs slightly from internally generated cash flows for non-financial firms. 
Chapter 3 discusses the differences in detail. 



16 
Baer and McElravey (1993) investigate the relation between growth and internally 
generated capital, and specifically address the issue of whether banks manage their assets 
as if external finance is costly. Moreover, they examine how changes in capital 
requirements might influence growth. Their results indicate that banks manage assets as if 
there are significant costs with issuing new equity, or in other words, internally generated 
capital strongly influences growth. They also find that growth explained by regulatory 
capital increased dramatically following the introduction of specific minimum capital 
standards in 1 98 1 . This suggests that banks view capital requirements as important, and 
that increases in standards may have significant negative effects on growth. 

A problem with their methodology is that the authors do not explicitly include 
market or bank level economic control variables, such as Tobin's Q, previous growth, or 
loan loss provisions. In addition their measure of internally generated capital is after 
deductions for dividend payments and loan loss provisions. Since these are both 
endogenous choice variables management has in its control, the inclusion of these items in 
regressions may lead to misleading results. The authors also do not mention liquidity, 
specifically securities holdings, playing a role in their investment model. This is surprising 
since similar studies for non-financial firms generally recognize firm liquidity as an 
important determinant of growth. Although it is conceivable that the availability of 
insured deposit financing obviates the need to worry about liquidity, the existence of 
capital requirements limits the amount of deposit financing allowable. As a result, liquidity 
should be an important contributor to investment. 



17 
Most prior studies on bank growth and capitalization rely on bank subsidiary data. 
However, if asymmetric information problems create capital market frictions, for most of 
banks these frictions will occur at the holding company level. This is because usually the 
parent company and not the subsidiary accesses the capital market. By definition, a bank 
holding company is any organization which owns or controls at least 25 percent of any 
class of voting stock of a commercial bank. 9 Since the 1970s, bank holding companies 
have dominated bank ownership, holding more than 90 percent of all commercial bank 
assets in the United States in 1993. While the formulation of holding companies allows 
banks to circumvent branching restrictions and other regulations imposed on individual 
banks, the operation of a holding company also provides a mechanism for consolidating 
the management and funding operations of individual subsidiary banks. 

In the absence of regulations restricting bank holding companies from managing 
capital on a consolidated basis, loan growth would be sensitive to the internally generated 
capital of the entire holding company. Moreover, subsidiary bank loan growth would be 
related primarily to the capitalization and earnings of the holding company, and not its 
own capitalization and earnings. However, some restrictions on inter-company transfers 
may potentially weaken the relation between subsidiary growth and holding company 
earnings. For example, if holding companies are restricted in their ability to upstream 
capital from subsidiaries, then each subsidiary's loan growth should partially depend on its 
own earnings. 



' The 1970 Amendments to the Bank Holding Company Act of 1956 provide a 
definition of a bank holding company and establishes limits on the activities in which 
holding companies may engage. 



18 
One restriction, in particular, is the requirement that all subsidiaries plus the 
holding company must individually maintain minimum capital ratios. This "building block" 
approach implies that failure of any subsidiary to meet capital standards will impede the 
holding company's ability to manage capital on a consolidated basis. 10 A second 
restriction is the Federal Reserve policy of viewing the holding company as a "source of 
strength" to individual subsidiaries. This creates an obligation for the holding company to 
downstream capital to inadequately capitalized subsidiaries. As a result, holding 
companies may not be able to allocate capital to subsidiaries with positive NPV projects. 
Finally, sections 23 A and 23B of the Federal Reserve Act place restrictions on inter- 
company transfers. Specifically, dividends, fees, and intercompany asset sales are 
restricted to transfers of less than 10 percent of the bank's capital." Again, these 
restrictions limit the ability of the holding company to allocate capital on a consolidated 
basis. 

I analyze the effects of capital market imperfections on the sensitivity of bank 
investment, at both the holding company and subsidiary level, to internally generated 
additions to capital. I assume that loan growth (net of loan losses) is the banking 
equivalent of investment by non-financial firms. 12 Given the existence of capital market 



10 See the Bank Holding Company Supervision Manual, sections 2010 and 4060.2. 

11 See section 2020. 1 of the Bank Holding Company Supervision Manual. 

12 Bank investment in real assets is less than 3 percent of total assets. Arguably, 
investment should consider securities. However, one motive for bank investment in 
securities is liquidity. I control for securities holdings as a form of bank liquidity when 
analyzing loan growth. 



19 
imperfections which create a wedge between internal and external finance, one would 
expect a positive relation between holding company loan growth and internally generated 
funds. Moreover, since capital requirements limit a bank's ability to substitute deposits for 
equity, I expect the sensitivity of loan growth to internally generated funds (investment- 
cashflow sensitivity) to be greatest for firms where the capital requirement is most binding. 

1 also examine how the nature of enforced capital requirements affects bank 
investment-cashflow sensitivities. In particular, with regulators mandating leverage-based 
capital standards, securities holdings may substitute for surplus capital as financial slack. 
This is because banks can fund growth through the liquidation of securities without 
changing required capital levels. Therefore, I expect the investment-cashflow sensitivities 
to be decreasing the in amount of securities (relative to assets) that banks hold on their 
balance sheets during the 1980s. However, beginning with the introduction of risk-based 
standards in 1990, securities holdings may no longer be as efficient at providing financial 
slack, and as a result I expect the investment-cashflow sensitivities to be unrelated to 
securities holdings in the 1 990s. 

A common criticism of studies of the cash flow sensitivity of investment is that 
current cash flow may be correlated with the profitability of investment opportunities. As 
a result, even without capital market imperfections, investment may be positively related 
to cash flows. I address this issue by including in the analysis the bank's market to book 
value of assets as a measure of Tobin's Q. In addition, I include the bank's previous 
growth as a second proxy for growth opportunities. I expect a positive relation between 
loan growth and both the market to book ratio and lagged loan growth. 



20 
An additional check on the existence of capital market frictions is to examine the 
operation of the internal capital market within a holding company. Specifically, if a 
positive correlation between cash flows and loan demand drives the relation between cash 
flows and loan growth, then subsidiary loan growth should be positively related to 
subsidiary cash flows. Moreover, holding company cash flows (net of the subsidiary's 
cash flows) will be related to loan growth at the subsidiary level only to the extent that 
they proxy for local demand characteristics. It is likely that holding company cash flows 
are a poorer proxy for local demand then subsidiary cash flows. Thus, in the absence of 
capital market imperfections, they would be expected to be less important than the 
subsidiary's own cash flows. Hence, a finding of holding company cash flows being more 
important than subsidiary cash flows would be consistent with the hypothesis of costly 
external capital. 

Furthermore, a finding of subsidiary loan growth being positively related to the 
cash flows of non-bank subsidiaries within the holding company can be interpreted as 
strong evidence that external finance is costly and holding companies operate and internal 
capital market. Indeed, it seems unlikely that in absence of costly external finance, 
subsidiary bank loan growth would be at all related to non-bank cash flows of the holding 
company since arguably these non-bank cash flows are less likely to proxy for local loan 
demand. 

As a final test on the existence of capital market frictions, I examine the 
information asymmetry surrounding external capital issuances. If the magnitude of the 
investment-cashflow sensitivity proxies for the severity of capital market frictions that 



21 
banks face, banks with a large investment-cashflow sensitivity are expected to be less 
willing to issue external capital. I develop a logit model which predicts banks' decision to 
issue external capital based on firm and market characteristics. A finding of a negative 
relation between the probability of issuance and the investment-cashflow sensitivity 
provides evidence that the investment-cashflow sensitivity proxies for the severity of 
information asymmetries. 

The severity of information asymmetries may also be related to the expected costs 
of bringing an external capital issue to the market. To test this hypothesis, I estimate the 
relation between investment-cashflow sensitivities and costs associated with security 
issuance. Following Calomiris and Himmelberg (1995), I estimate anticipated 
underwriting fees based on firm characteristics, after controlling for selectivity bias. In a 
likewise fashion, I estimate expected abnormal stock returns associated with the 
announcement of a security issuance. A finding that banks that anticipate larger 
underwriting fees or more negative abnormal stock returns have higher investment- 
cashflow sensitivities would provide additional support for the hypothesis that expected 
external finance costs affect banks' dependence on internally generated funds. 



CHAPTER 3 
DATA 

I collect bank holding company data from the Federal Reserve Y-9 tapes from 
1982-1994 (annual observations). Banks included in the sample are required to have a 
minimum of two years of data, a non-negative book value of equity, and an available 
market value of common equity. All stock price data come from the CRSP and NASD 
master tapes. The final holding company sample contains 289 banks and 2229 
observations. 

Subsidiary bank data are collected from the Federal Reserve Reports of Income 
and Condition (Call Reports). Call report data is only available from 1985-1989. 
Subsidiary banks are required to have at least two year-end observations and be part of a 
multiple bank holding company. I restrict the sample to multi-bank holding companies 
because I am interested in examining whether holding companies act as an internal capital 
market. In addition, the subsidiaries must be part of a holding company included in the 
holding company sample described above. The subsidiary bank sample contains 2339 
different bank subsidiaries of 215 holding companies yielding 7023 observations. 

Studies of investment spending for nonfinancial firms consider investment to be a 
function of internally generated funds after controlling for firm growth opportunities (see 
for example Fazzari, et. al. (1988)). Typically, investment is considered changes in 
property, plant, and equipment, deflated by the firm's capital stock at the beginning of the 

22 



23 
period. Capital stock is usually proxied by property, plant, and equipment. In addition, 
the existing literature generally deflates internally generated funds by the capital stock. I 
consider bank investment to be the change in loans outstanding, and the capital stock to be 
the beginning of period loans outstanding. Therefore, investment (loan growth) is defined 
as the percentage change in loans outstanding. 

The appropriate measure of internally generated funds for banking firms differs 
slightly from the measure used in studies of nonfinancial firms. Specifically, studies of 
nonfinancial firms generally measure internally generated cash flows as net income before 
extraordinary items plus depreciation. However, banks may not be as constrained by cash 
flow as nonfinancial firms because of the availability of insured deposit financing. 
Nevertheless, they are constrained by the amount of debt financing they can utilize. 
Regulations mandate capital requirements which limit banks' ability to borrow, and thus 
banks should be concerned with the amount of regulatory capital that they generate. I 
measure internally generated funds as net income before extraordinary items plus 
depreciation and additions to loan loss provisions (since loan loss provisions are a non- 
cash expense and are included in regulatory capital), and I scale this measure by the 
beginning of period loan balance. 1 To control for differences in investment opportunities, 
I use the holding company's market to book ratio ( a proxy for Tobin's Q) at the end of 
the prior year and the bank's previous period loan growth. Furthermore, I include the log 
of assets as a control for economies of scale. 



Results are similar if I do not include additions to loan losses as part of internally 
generated funds. The results are also similar if I deduct dividend payments from internally 
generated funds. See Chapter 4 for more detail. 



24 
To determine the effect of capitalization on loan growth, I estimate surplus capital 
for all banks, both holding companies and subsidiaries. Surplus capital is defined as the 
bank's beginning of year capital ratio minus the end of year required ratio. 2 I choose the 
end of year required ratio because this requirement is always at least as strict as the 
current requirement. This assumes that banks have perfect foresight regarding short term 
capital requirements, earnings and growth. Tests rely on the total or Tier II capital ratio. 3 
The Tier II ratio is chosen because regulations currently allow banks to pass the Tier I 
ratio and yet fail the Tier II ratio, but not the reverse. Specifically, the secondary portion 
of Tier II capital (loan losses and subordinated debt) is restricted to be no greater than the 
primary portion of capital. In addition, current regulations require 4 percent Tier I and 8 
percent Tier II capital ratios. Hence it is obvious that banks which pass the Tier II 
requirement must by definition have passed the Tier I requirement. 

Surplus capital provides an indication of financial slack, i.e., the cushion banks 
have in their capital ratios (similar to the cash and liquid assets measure used in studies of 
nonfinancial firms). I also include a dummy variable, BIND, which equals one if capital 
surplus is non-positive, and zero otherwise. This variable indicates whether a bank failed 
to meet the minimum capital requirement in any given year. 



2 Data for risk-based capital ratios are not available. Therefore, I rely on a 
methodology presented by Takeda (1994) to estimate risk-based ratios. See Appendix for 
a description of this methodology. 

Tier II capital is defined as total equity plus subordinated notes plus the 
allowance for loan losses all scaled by assets (either total or risk- weighted). Total equity 
includes both common and preferred equity. Tests were also performed using the primary 
or Tier I ratio (simply total equity over assets), with similar results. 



25 
Required capital ratios have varied over time. From 1981-1989, regulators 
enforced leverage-based capital ratios which they define as total equity plus subordinated 
notes plus the allowance for loan losses, all divided by total assets. Required ratios were 
5.5 percent from 1981-1984 and 6 percent from 1985-1989. In the 1990s, risk-based 
capital ratios became enforced, with the only change in the calculation of the capital ratio 
being the substitution of risk- weighted assets for total assets. 4 Required ratios were 7.25 
percent from 1990-1991, and 8 percent from 1992-1994. 

In addition, I study announcements of all external security offerings which 
augment regulatory capital (except for initial public offerings) by bank holding companies 
that were publicly traded in the United States from 1982-1994. These offerings consist of 
common stock, preferred stock, or subordinated notes. The initial sample of issuances 
was collected from the Investment Dealer 's Digest (IDD). I searched Dow Jones News 
Retrieval for the announcement of these issuances and used these dates as the initial 
announcement date. If no mention of the offering was found on Dow Jones News 
Retrieval, I used the registration date listed in the IDD. The final sample contains 461 
security offerings by 157 different bank holding companies. 

To calculate abnormal returns following the announcement of a security offering, I 
use the standard event study methodology (see Asquith and Mullins (1986)). All stock 
return data are collected from either the CRSP or NASD data tapes. Abnormal returns for 
security / on event date / are defined as: 



See Appendix for estimation of risk- weighted assets. 



26 

where Rj, and Rm, are the rate of return on security / and the return on the CRSP equally 
weighted index on event day t respectively. The coefficients a and P are ordinary least 
squares estimates of the intercept and slope of the market model regression. The 
estimation period used for the market model comes from the period t= -100 through t= - 
20 (where t=0 equals the event day). 

The average abnormal return for a portfolio of N securities is: 

AAR = -T AR, 
1 NU " 

The test statistic, Z„ for AAR, is based on the standardized abnormal return SARj, 5 , has a 
unit-normal distribution, and is calculated as: 

Z t = £ SAR H I JN 



Where SAR^ = ARj, / S, 



S it = [c 2 [i + -L + ^2L5J iii/2 
80 g o JJ 

E (R mk -R m ? 



and Sj is the residual standardized error from the market model regression, R^ the return 
on the market portfolio for the £th day of the estimation period, and R„, the average return 
of the market portfolio for the estimation period. 



CHAPTER 4 
BANK HOLDING COMPANY ANALYSIS 

Table 1 provides descriptive statistics for the bank holding company sample. The 
holding companies in my sample are relatively large, with median assets of over $2.6 
billion during the entire sample period. As expected, loans make up the majority of bank 
assets, with more than 62 percent of aggregate bank assets allocated to loans for the full 
sample. In addition, securities holdings make up a large portion of bank assets, 
comprising more than 14 percent of aggregate bank assets. For the full sample, the 
median bank holding company's Tier II capital ratios exceeded the regulatory minimum by 
approximately two percentage points. Furthermore, only about 6 percent of banks failed 
to meet minimum capital standards. 

Loan growth at the holding company level averaged about 6 percent a year. 
Internal additions to capital for the average and median bank was approximately 1.5 
percent of loans per year. Given capital requirements less than 8 percent, internal 
additions to capital appear, on average, to be sufficient to support the observed asset and 
loan growth. 

One purpose of this paper is to examine possible effects of changes in capital 
regulation on loan growth. From 1982-1994, capital regulation can be classified into three 
regimes. The first, from 1982-1984, marks the introduction of minimum leverage-based 
capital standards. Coincidentally, this period also corresponds with the announcement of 

27 



28 



Table 1 
Descriptive statistics (means, with medians in parentheses) for 289 publicly traded bank 

holding companies. 3 



variable 


full sample 


1982-1984 


1985-1989 


1990-1994 


Total Assets (millions) 


10,300 
(2,621) 


7,911 
(2,074) 


9,260 
(2,545) 


12,700 
(3,619) 


Loan Growth b 


0.062 
(0.076) 


0.109 
(0.121) 


0.078 * 
(0.090) * 


0.020 * 
(0.029) * 


Internal Additions to 
Capital/ Loans,., 


0.014 
(0.016) 


0.017 
(0.017) 


0.014 * 
(0.016) * 


0.013 
(0.016) 


Market / Book Assets'* 


1.005 
(0.999) 


0.986 
(0.985) 


1.010 * 
(1.004)* 


1.010 
(1.003) 


Book Capital in Excess 
of Requirement / Assets e 


0.024 
(0.020) 


0.019 
(0.016) 


0.020 
(0.018) 


0.031 * 
(0.028) * 


Percentage with Capital 
less than requirement. 


5.65% 


8.12% 


3.83% * 


6.41%* 


Aggregate Industry 
Loans / Assets 


62.28% 


60.14% 


64.42% 


61.25% 


Aggregate Industry 
Securities / Assets 


14.62% 


11.29% 


13.12% 


16.87% 


Number of Observations 


2229 


431 


940 


858 



a. Data are from the Federal Reserve Y-9 tape. 

b. Loan growth equals change in total loans outstanding divided by loans outstanding at time t- 1 . 

c. Internal additions to capital equals net income plus changes in loan loss provisions (up to regulatory 
maximum). 

d. Market to book value of assets equals (Total Assets - Book Equity + Market Equity) / Total Assets. Market 
Equity equals the market value of common equity from CRSP. The ratio is calculated at year end for the prior 
year. 

e. Book capital in excess of requirement equals the bank's book capital for regulatory minimum Tier II capital 
ratio. Tier II capital equals common stock, preferred stock, plus eligible subordinated debt and loan loss 
reserves. For the period 1982-1984 the requirement is 5.5% of total assets. For 1985-1989 the requirement is 
6%. Beginning in 1 990, the requirement is based on risk-weighted assets. For 1 990- 1 99 1 , the minimum is 
7.25% of risk-weighted assets, while from 1992-1994 the minimum is 8%. 

* mean or median significantly different from previous time period at better than the 5% level. 



29 
the 'too big to fail' policy in which certain banks were deemed too important to be 
allowed to fail. 1 O'Hara and Shaw (1990) document that following this announcement, 
large banks experienced an increase in stock price, which they attribute to be due to the 
expanded conjectural guarantees. The second regime lasts from 1985-1989, when 
regulators increased the minimum capital requirement from 5.5 to 6 percent. In addition, 
regulators attempted to remove the expanded conjectural guarantees implied by the 'too 
big to fail' policy. Finally, the third regime starts in 1990 and begins the era of risk-based 
capital standards. 

Table 1 provides the descriptive statistics by the three regulatory regimes. Notice 
that with each regime, loan growth has declined (both average and median). If bank 
growth opportunities have also declined, this could explain the decrease in loan growth. 
Market to book ratios (a proxy for Tobin's Q) have increased since the early 1980s, 
indicating that overall growth opportunities have improved. However, a potential 
explanation for why overall growth opportunities improved while loan growth suffered is 
that off-balance sheet growth drives the increase in market to book ratios. 

A second possibility for why loan growth has suffered could be a simultaneous 
decline in bank internal additions to capital. While it's true that internal additions to 
capital declined since the first regime, the amount of the decline hardly matches the 
substantial pace of the decline in lending. 



This policy implies that regulators will attempt to bail out any large institution 
which is insolvent. Furthermore, since the FDIC effectively insured all bank debt (not just 
small deposits) in the Continental Illinois case, management of large banks may have 
reasonably assumed that the federal safety net had been expanded. 



30 
Changes in capital regulation could induce a slowdown in lending if banks become 
inclined to increase surplus capital. First, if penalties from being undercapitalize increase, 
then banks will desire a larger buffer from regulatory intervention. Second, if risk-based 
capital standards reduce the effectiveness of securities as financial slack, banks will require 
more surplus capital as compensation for their lost liquidity. While average and median 
surplus capital do not appear to be any different in the first or second regimes, since 1990 
banks have increased surplus capital by more than one percentage point. The number of 
capital deficient banks increased from just less than 4 percent in the mid 1980s to more 
than 6 percent in the 1990s. Moreover, from 1990 to 1992, almost 10 percent of banks 
failed capital standards (not reported). 

If risk-based standards increase the attractiveness of securities relative to loans, 
banks may increase the proportion of securities in their portfolio. Consistent with this 
hypothesis, securities holdings increased from about 13 to almost 17 percent of aggregate 
bank assets, while loans fell from 64 to 61 percent of aggregate assets following the 
introduction of risk-based standards in 1990. Thus the change to risk-based capital may 
have caused many banks to fail capital standards, induced banks to desire a larger surplus 
capital, and given banks incentives to shift assets out of loans and into securities, all of 
which may have contributed to the concurrent decline in loan growth. 

If capital market imperfections create a wedge between internal and external 
finance costs for banks, then inadequately capitalized banks may be more likely to pass up 
profitable new lending opportunities than adequately capitalized banks. To test this 
hypothesis, I examine whether loan growth is related to capitalization for the banks in my 



31 
sample. However, loan growth and capitalization may be correlated for other reasons. In 

particular, loan losses are likely to be correlated with loan demand, causing a positive 

correlation between loan growth and capitalization. Therefore, I also examine the relation 

between internal additions to capital and bank capitalization. 

Table 2 presents the results of this analysis. The top portion of the table analyzes 
differences in holding company loan growth in three different capitalization categories: 
failure to meet capital requirements, capital in excess of requirements by 2 percentage 
points or less, and capital in excess of requirements by greater than 2 percentage points. 
Loan growth at inadequately capitalized banks was significantly less than loan growth at 
either of the other two categories. In addition, there is no difference between loan growth 
at either of the two adequately capitalized categories. Moreover, as shown in the bottom 
portion of the table, the amount of internal capital generation increases significantly with 
capitalization, suggesting that performance strongly influences capital adequacy. 

That loan growth is correlated with capitalization is consistent with capital 
requirements and costly external finance constraining loan growth. However, as 
mentioned above the finding that internal additions to capital is correlated with 
capitalization may drive this result. Since loan losses and poor performance are likely to be 
correlated with weak loan demand, the positive relation between loan growth and 
capitalization may reflect demand as opposed to supply characteristics. To address these 
concerns, I examine the relation between loan growth and internal additions to capital. 

In Table 3, 1 present the results of a fixed-effects regression relating loan growth 
to internal additions to capital, the market to book value of assets, previous loan growth, 



32 

Table 2 
Differences in loan growth and internal additions to capital based upon whether minimum 
capital requirements are binding for a sample of 289 bank holding companies from 1982- 

1994. 



Loan Growth 




Mean 


Median 


1 . Capital less than or equal to regulatory 
minimum, N= 126 


-0.032% 


-0.034 


2. Capital greater than regulatory minimum 
by 2% or less, N=968 


0.066 


0.083 


3. Capital greater than regulatory minimum 
by more than 2%, N=l 143 


0.069 


0.077 


Test statistic of difference between 1 and 2. 


t=7.64 


z=7.75 


Test statistic of difference between 1 and 3. 


t=7.97 


z=8.01 


Test statistic of difference between 2 and 3. 


t=0.72 


z=0.08 


Internal Additions to Capital 




Mean 


Median 


1 . Capital less than or equal to regulatory 
minimum, N= 107 


0.002 


0.005 


2. Capital greater than regulatory minimum 
by 2% or less, N=908 


0.015 


0.013 


3. Capital greater than regulatory minimum 
by more than 2%, N=93 1 


0.017 


0.019 


Test statistic of difference between 1 and 2. 


t=7.23 


z=8.95 


Test statistic of difference between 1 and 3. 


t=9.83 


z=l 1.10 


Test statistic of difference between 2 and 3. 


t=6.92 


z=10.28 



33 

Table 3 

Fixed effects regressions relating loan growth to internal additions to capital, capital 

requirements, and firm financial characteristics. The sample consists of 289 bank holding 

companies from 1982-1994 (standard errors in parentheses). 



Dependent Variable = (Loans, - Loans,., ) / Loans,., 


Coefficient 


(1) 


(2) 


Additions to Capital / Loans,.,* 


4.771 ** 
(0.269) 


3.906 ** 
(0.198) 


Surplus Capital / Assets,., b 


0.824 ** 
(0.155) 




Bind' 




-0.061 ** 
(0.009) 


Surplus Capital *Additions to 
Capital / Loans,., 


-27.80 ** 

(4.471) 




Bind * Additions to Capital / Loans,., 




1.006* 
(0.512) 


Securities / Assets,., 


0.138** 
(0.039) 


0.133 ** 
(0.039) 


Market / Book Assets,., 


0.270 ** 
(0.049) 


0.260 ** 
(0.049) 


log (Assets,.,) 


-0.063 ** 
(0.005) 


-0.064 ** 
(0.005) 


Lag loan growth 


0.078 ** 
(0.009) 


0.078 ** 
(0.009) 


R 2 


0.383 


0.385 


N (categories) 


1987(289) 


1987(289) 


F statistic, Bank dummies 


2.278 ** 


2.571 ** 



a. Additions to capital equals net income plus changes in loan loss provisions (up to regulatory maximum). 

b. Surplus capital equals actual capital less capital required to meet minimum regulatory standards. 

c. Bind=l if surplus capital is less than or equal to zero, =0 otherwise. 
*, ** denote significance at the 5% and 1% levels respectively. 



34 
bank size, asset composition, and two variables designed to measure the extent to which 
the bank faces binding capital requirements. These two variables are surplus capital, 
defined as the difference between bank capital ratios and the required ratio, and a dummy 
variable that takes on the value of one if surplus capital is non-positive and zero otherwise. 
Furthermore, I interact these two variables with internal additions to capital to investigate 
whether the cashflow sensitivity of loan growth varies depending on whether the holding 
company faces a binding capital constraint. I assume that the lower the surplus capital, the 
greater the likelihood that capital requirements are binding. These are the banks that are 
most likely to constrain loan growth because of high external finance costs. 

As shown in Table 3, loan growth is positively related to internal additions to 
capital even after controlling for differences in growth opportunities with the market to 
book ratio and previous loan growth. This is consistent with external finance being costly 
relative to internal finance. In addition, loan growth is positively related to surplus capital, 
and is significantly lower for holding companies which fail to meet capital requirements. 
Furthermore, the sensitivity of loan growth to internal additions to capital decreases as 
surplus capital increases. Notice a similar result that the sensitivity is significantly higher 
for capital deficient banks. These results are consistent with the hypothesis that the loan 
growth of capital constrained banks is significantly more sensitive to internally generated 
funds than it is for banks that maintain adequate capital. This also suggests that increases 
in capital standards may influence loan growth by diminishing surplus capital for all banks. 
Following an increase in capital standards the percentage change in the predicted 
sensitivity of loan growth to internal additions to capital will be largest for banks that had 



35 
the largest surplus capital (lowest sensitivity) before the change. This is consistent with 
Passmore and Sharpe's hypothesis that the decline in lending may be most severe at well 
capitalized institutions. 

Since banks may be able to fund loan growth by selling securities holdings, the 
sensitivity of loan growth to internal additions to capital may also be negatively related to 
securities holdings. 2 On the other hand, securities may only provide this type of financial 
slack to banks that are not constrained by capital requirements. That is, capital 
constrained banks need to increase capital, and therefore selling securities to fund growth 
may not be an option. To investigate these possibilities, Table 4 presents regression 
results relating loan growth to the same measures used in Table 3, plus six additional 
interaction variables. These interaction variables are designed to explain the role of 
securities as financial slack. In particular, I expect that the sensitivity of loan growth to 
internal additions to capital to be decreasing in the amount of securities holdings, and this 
relationship to be less important for banks which fail to maintain minimum capital ratios. 

Like the results presented in Table 3, Table 4 provides evidence that banks view 
external finance as more expensive than internal finance as indicated by the positive 
coefficient on internal additions to capital. Moreover, these results support the claim that 
surplus capital is positively related to loan growth, and negatively related to the sensitivity 
of loan growth to internal additions to capital. In three of the four regressions presented, 
the coefficient on the interaction between internal additions to capital and securities is 



Even with risk-based standards, this may be true since banks can sell securities 
with a non-zero risk weight or that have a capital gain to fund loan growth without 
penalizing capital ratios. 



36 

Table 4 

Fixed effects regressions relating loan growth to internal additions to capital, capital 

requirements, and firm financial characteristics. The sample consists of 289 bank holding 

companies from 1982-1994 (standard errors in parentheses). 



Dependent Variable = (Loans, - Loans,., ) / Loans,., 


coefficient 


(1) 


(2) 


(3) 


(4) 


Additions to Capital / Loans,.," 


4.737 ** 
(0.316) 


4.446 ** 
(0.345) 


4.763 ** 
(0.419) 


4.623 ** 
(0.351) 


Surplus Capital / Assets,., b 


0.678 ** 
(0.153) 




0.661 * 
(0.298) 




Bind c 




-0.061 ** 
(0.009) 




-0.012 
(0.019) 


Surplus Capital * Additions to 
Capital /Loans,., 


-18.89** 
(4.417) 




-19.47* 
(8.964) 




Bind * Additions to Capital / 
Loans,., 




0.916 
(0.514) 




-0.388 
(1.172) 


Securities / Assets,., 


0.206 ** 
(0.044) 


0.182** 
(0.046) 


0.204 ** 
(0.059) 


212** 
(0.475) 


Securities * Additions to 
Capital / Loans,., 


-2.763 * 
(1.288) 


-2.619** 
(1.375) 


-2.876 
(1.906) 


-3.441 ** 
(1.401) 


Surplus Capital * Securities / 
Assets,., 






0.077 
(1.329) 




Bind * Securities / Assets,., 








-0.318** 
(0.110) 


Surplus Capital * Securities * 
Additions to Capital / Loans,., 






1.749 
(34.88) 




Bind * Securities * Additions 
to Capital / Loans,., 








8.313 
(6.750) 


Market / Book Assets,., 


0.287 ** 
(0.049) 


0.256 ** 
(0.049) 


0.287 ** 
(0.049) 


0.260 ** 
(0.049) 


log (Assets,.,) 


-0.066 ** 
(0.005) 


-0.064 ** 
(0.005) 


-0.066 ** 
(0.005) 


-0.065 ** 
(0.005) 


Lag loan growth 


0.080 ** 
(0.009) 


0.077 ** 
(0.009) 


0.080 ** 
(0.009) 


0.076 ** 
(0.009) 


R 2 


0.373 


0.386 


0.373 


0.389 


N (categories) 


1992(289) 


1987(289) 


1992(289) 


1987(289) 


F statistic, Bank dummies 


2.304 ** 


2.489** 


2.301 ** 


2.502 ** 



a. Additions to capital equals net income plus changes in loan loss provisions (up to regulatory maximum). 

b. Surplus capital equals actual capital less capital required to meet minimum regulatory standards. 

c. Bind=l if surplus capital is less than or equal to zero, =0 otherwise. 
*, ** denote significance at the 5% and 1% levels respectively. 



37 
negative and significantly different from zero at the one percent level. This is consistent 
with the hypothesis that securities holdings serve as a buffer stock against funding 
shortages. The negative coefficient on the interaction between BIND and securities 
indicates that the role of securities as financial slack is less important for capital deficient 
banks. In particular, the estimated coefficient on securities holdings for capital deficient 
banks (by combining the two coefficients) is not significantly different from zero. These 
results suggest that both surplus capital and securities holdings serve as liquidity by 
decreasing banks' dependency on internally generated additions to capital. 

This paper is interested in examining the effect of changes in capital regulations on 
loan growth, specifically with regard to risk-based capital standards. Specifically, with 
regulators enforcing risk-based standards, the role of securities as financial slack may be 
significantly diminished. To investigate further, Table 5 presents results of fixed-effects 
regression models of loan growth to the same measures used in Table 3, while allowing 
coefficients on key explanatory variables to change with each regulatory regime. This will 
enable me to investigate if changes in regulation altered the determinants of the loan 
growth equation. 

Surprisingly, results indicate that in the first regime (1982-1984), capital surplus 
did not influence loan growth. This is consistent with banks believing that capital 
requirements were not stringently enforced. A possible explanation for this is the 
expanded conjectural guarantees implied by 'too big to fail.' In regimes two (1985-1989) 
and three (1990-1994), surplus capital is positively related to loan growth and negatively 
related to the sensitivity of loan growth to internal additions to capital. On the other hand, 



38 

Table 5 

Fixed effects regressions relating loan growth to internal additions to capital, capital 

requirements, and firm financial characteristics. The sample consists of 289 bank holding 

companies from 1982-1994 (standard errors in parentheses). 



Dependent Variable = (Loans, - Loans,., ) / Loans,., 


coefficient 


(1) 


(2) 


Additions to Capital / Loans,., 


5.348** (0.351) 


4.783 ** (0.346) 


Surplus Capital / Assets,., * timel 


0.238 (0.549) 




Surplus Capital / Assets,., * time2 


1.987** (0.290) 




Surplus Capital / Assets,., * time3 


0.767** (0.179) 




bind * timel 




0.026 (0.028) 


bind * time2 




-0.055** (0.015) 


bind * time3 




-0.084** (0.014) 


Surplus Capital * timel * Additions to Capital/Loans 


-4.385 (28.87) 




Surplus Capital * time2 * Additions to Capital/Loans 


-61.31** (13.10) 




Surplus Capital * time3 * Additions to Capital/Loans 


-28.16** (5.028) 




bind * timel * Additions to Capital 




-0.974 (2.009) 


bind * time2 * Additions to Capital 




0.513 (0.782) 


bind * time3 * Additions to Capital 




-0.149 (0.740) 


Securities / Assets,., * timel 


0.553 ** (0.875) 


0.449 ** (0.079) 


Securities / Assets,., * time2 


0.187** (0.053) 


0.256 ** (0.050) 


Securities / Assets,., * time3 


0.013 (0.049) 


0.036 (0.048) 


Securities * timel * Additions to Capital/Loans 


-11.30** (4.196) 


-8.119** (3.235) 


Securities * time2 * Additions to Capital/Loans 


-7.718** (1.808) 


-3.275** (1.620) 


Securities * time3 * Additions to Capital/Loans 


2.360 (0.048) 


-0.038 (1.451) 


Market / Book Assets,., 


0.231 ** (0.048) 


0.223 ** (0.049) 


log (Assets,.,) 


-0.024 ** (0.007) 


-0.024 ** (0.007) 


Lag loan growth 


0.058** (0.010) 


0.058** (0.010) 


R 2 


0.439 


0.431 


N (categories) 


1990(289) 


1990(289) 


F statistic, Bank dummies 


2.022 ** 


2.152** 



denote significance at the 5% and 1% levels respectively. 



39 
securities holdings appear to be significant contributors of financial slack up until the 
1990s. Specifically, the regime three coefficients on securities holdings (and the 
interaction variables) are not significantly different from zero. Moreover, these 
coefficients are significantly different from previous period coefficients suggesting a real 
change in the value added of securities holdings. This suggests that the change to risk- 
based standards significantly altered the role of securities as liquidity. As a result, this 
change in regulatory regimes may have induced a slowdown in bank growth. 

The results presented in Tables 3-5 indicate a negative relation between surplus 
capital and the sensitivity of loan growth to internal additions to capital. In addition, the 
results demonstrate that securities holdings are also negatively related to this sensitivity, at 
least before the introduction of risk-based capital standards. However, whether a firm's 
overall investment-cashflow sensitivity is negatively related to surplus capital, after 
controlling for the effect of securities remains a question. Table 6 presents results of the 
predicted sensitivity of loan growth to internal additions to capital from regression (1) in 
Table 5. 3 To estimate this overall sensitivity, I simply calculate the total effect of internal 
additions to capital by multiplying the coefficient estimates on the interaction terms by the 
appropriate variables, and adding these products to the coefficient of additions to capital. 
This allows the estimate of the investment-cashflow sensitivity to vary by bank and year. 
Notice that the mean and median investment-cashflow sensitivity is largest for banks that 
fail to meet minimum capital standards (significantly different from the sensitivity for the 



Results are similar if the investment-cashflow sensitivities are estimated from 
regressions in Table 4. 



40 



Table 6 
Characteristics of predicted investment-cashflow sensitivity 



Variable=Predicted Investment-Cashflow Sensitivity estimated from coefficients on Additions to Capital 
and interaction terms from regression (1), Table 5. 


Descriptive Statistics, by Capitalization 


mean 


median 


full sample, N=2229 


3.706 


3.774 


1 . Capital less than or equal to regulatory minimum, N= 1 26 


4.534 


4.559 


2. Capital greater than regulatory minimum by 2% or less, N=960 


4.003 


4.019 


3. Capital greater than regulatory minimum by more than 2%, N=l 143 


3.365 


3.469 


Test statistic of difference between 1 and 2. 


t=19.94 


z=15.44 


Test statistic of difference between 1 and 3. 


t=39.37 


z= 18.20 


Test statistic of difference between 2 and 3. 


t=36.66 


z=32.05 



Table 7 
Fixed effects regressions relating the predicted investment-cashflow sensitivity to off- 
balance sheet assets and other firm financial characteristics. Off-balance sheet assets data 
are available beginning in 1991. The sample consists of 230 bank holding companies from 

1991-1994 (standard errors in parentheses). 



Dependent Variable=Predicted Investment-Cashflow Sensitivity estimated from coefficients on Additions to 
Capital and interaction terms from regression (1), Table 5. 


Variable 


(1) 


(2) 


Constant 


3.261 ** 
(0.052) 


8.795 ** 
(1.325) 


Off Balance Sheet Assets,.,/ Assets,., 


0.875 ** 
(0.227) 


0.661 ** 
(0.207) 


Bind 




0.548 ** 
(0.059) 


Log (Assets,.,) 




-0.364 ** 
(0.087) 


R 2 


0.097 


0.220 


N 


651 


651 


F statistic, Bank dummies 


13.93 ** 


13.62** 



*, ** denote significance at the 5% and 1% levels respectively. 



41 
foil sample, and from adequately capitalized banks at better that the one percent level). 
Moreover, the sensitivity decreases in groups based on capitalization. Therefore, even 
after controlling for the effect of securities, the investment-cashflow sensitivities are 
negatively related to surplus capital. 

This overall investment-cashflow sensitivity may proxy for the severity of capital 
market frictions. If a larger sensitivity indicates more severe information asymmetries, 
banks with higher investment-cashflow sensitivities may face higher costs of external 
finance. As a result these banks may have increased incentives to hedge the risks inherent 
in their asset portfolios. This implies that the amount of off-balance sheet assets as a 
proportion of total assets may be positively related to the investment-cashflow sensitivity. 
Table 7 presents fixed-effects regression results relating the investment-cashflow 
sensitivity to off-balance sheet assets. Because of reporting requirements, complete off- 
balance sheet data are only available beginning in 1991. Results indicate that banks with 
larger investment-cashflow sensitivities use more off-balance sheet assets, presumably to 
hedge against funding shortages. These results also provide evidence that larger banks are 
less constrained by internally generated funds. All together, these results support the 
hypothesis that the investment-cashflow sensitivity proxies for the severity of information 
asymmetries. 

As a check on the robustness of the results presented above, I perform a series of 
tests intended to examine the stability of the coefficient estimates. Results for these tests 
are not reported, however, tables are available upon request. To control for the possibility 
that results are being driven by merger and acquisition activity, I perform all above tests 



42 
scaling observations by year end data. Results are qualitatively similar. I also perform the 
regressions limiting bank loan growth to be less than 25 percent. In addition, I choose 
other various limits for loan growth, none of which make a substantial impact on the 
results. As a control for possible bias due to firms not surviving the sample period, I 
estimate the basic regressions presented in Table 3 for the 97 banks which survive the 
entire period. Results are consistent with previous results. 

One possible difference for the relation between investment and cash flow for 
banking firms relative to nonfinancial firms is that a large portion of the cash flow from a 
new investment may be received up front. In particular, new loan originations usually 
generate immediate fee income for banks, unlike investment for industrial firms which may 
take years after the initial investment before income is realized. To investigate this further, 
I examine the degree of autocorrelation in additions to capital. I find that there is a strong 
one period correlation of more than 50 percent. Additionally, the second and third lagged 
observations are correlated at more than 10 percent, although the partial correlation 
coefficient is very small after the first period. Moreover, the results of an ARMA model 
using four lagged observations are consistent with a strong one period correlation, with 
subsequent periods significantly related, although to a much smaller extent. 

A possible interpretation of these results is that the positive relation between loan 
growth and internal additions to capital is not due to firms investing when they generate 
income, rather they generate income when they invest. To address this concern, I estimate 
the basic regressions replacing additions to capital with a lagged observation of additions 
to capital. Results are consistent with previous results. 



43 
Furthermore, the formulation of internal additions to capital assumes that all bank 
income which augments capital is available to fund loan growth. This implies that banks 
may alter dividend policy to meet investment needs. However, it is possible that banks 
find dividend cuts prohibitively expensive, and therefore do not vary dividend policy. In 
addition, the inclusion of loan losses may bias estimates if firms manipulate these 
provisions to their advantage. Therefore, I repeat the basic regression using three 
variations of internal additions to capital. Variation one is simply the original definition 
minus dividend payments. Variation two is defined as net income minus dividends (no 
treatment for loan loss provisions). Finally, variation three is simply net income. Results 
are qualitatively similar. 

Loan growth may measure investment with error. Specifically, banks can invest in 
loan commitments, which generate fee income and now require capital backing. Thus, I 
estimate the regressions replacing loan growth with growth in loans and loan 
commitments. Because of reporting requirements, growth in loan commitments is only 
available beginning in 1990. Results from a heteroskedastic consistent model (I choose not 
to use fixed-effects due to the small number of observations per firm) conform with 
previously reported results, and support the hypothesis that external finance is costly and 
that the sensitivity of investment to internal additions to capital is negatively related to 
surplus capital. Moreover, securities holdings are not related to growth in this particular 
model. This provides additional support that with risk-based capital standards, the role of 
securities as financial slack has been diminished (since data is only available for these tests 
in the 1990s). 



CHAPTER 5 
BANK SUBSIDIARY ANALYSIS 

The above results are consistent with capital regulation significantly affecting bank 
loan growth. Moreover, these results lend credence to the argument that banks find it 
more costly to raise capital externally than through internal funds. To further examine this 
issue, this chapter analyzes bank subsidiary loan growth as it relates to holding company 
and subsidiary characteristics. Table 8 documents the descriptive statistics for bank 
subsidiaries in my sample. Loan growth averaged about 9.5 percent a year, while internal 
additions to capital averaged around 1.5 percent of total loans. Furthermore, the median 
subsidiary and holding company's Tier II capital ratio exceeded the regulatory minimum 
by slightly less than 2 percentage points. 

The bottom section of Table 8 describes differences in subsidiary loan growth 
based on capitalization of both holding companies and subsidiaries. The median loan 
growth of subsidiaries whose holding company was inadequately capitalized was just over 
1 percent. However, median growth of subsidiaries whose holding company was 
adequately capitalized was significantly greater, at over 7.5 percent. In addition, there 
appears to be no difference in subsidiary loan growth based on whether the subsidiary 
itself maintains adequate capital ratios. These results are consistent with bank holding 
companies operating capital on a consolidated basis. 



44 



45 



Table 8 
Descriptive statistics of subsidiaries of 215 publicly traded multiple bank holding 

companies from 1985-1989* 



variable 


mean 


median 


Subsidiary Total Assets (millions) 


250 


99 


Internal Additions to Capital / Loans Bank 


0.018 


0.018 


Internal Additions to Capital / Loans H . net b 


0.014 


0.016 


Internal Additions to Capital / Loans^,,^,^ 


0.004 


0.004 


Securities / Assets 


0.219 


0.205 


Lead Bank Assets / Holding Company Assets 


0.354 


0.244 


(Book Capital in Excess of Requirement / Assets) Bank 


0.024 


0.018 


(Book Capital in Excess of Requirement / Assets) H 


0.019 


0.017 


Subsidiary Bank Loan Growth 


0.096 


0.075 


Subsidiary Bank Loan Growth if holding company 
capital is less than regulatory minimum, N=240 


0.028 


0.012 


Subsidiary Bank Loan Growth if holding company 
capital is greater than regulatory minimum, N=7037 


0.098 


0.076 


Test Statistic of Difference in Subsidiary Loan Growth 
based on holding company capitalization 


t=5.34 


z=5.48 


Subsidiary Bank Loan Growth if its capital is less than 
regulatory minimum, N=275 


0.095 


0.073 


Subsidiary Bank Loan Growth if its capital greater 
than regulatory minimum, N=7002 


0.111 


0.108 


Test Statistic of Difference in Subsidiary Loan Growth 
based on its own capitalization 


t=0.84 


z=1.6 



a. Data are from the Federal Reserve Reports of Income and Condition (Call Reports). 

b. Internal Additions to Capital H-Net equals holding company additions to capital less the bank's additions to 
capital divided by holding company loans less loans of the subsidiary bank. 

c. Internal Additions to Capital non-bank equals holding company additions to capital net of the aggregate 
additions to capital of all bank subsidiaries divided by holding company loans less loans of the subsidiary bank. 



46 
As described in the previous chapter, loan growth may be related to capitalization 
for reasons other than costly external finance. In particular, this relationship may arise due 
to bank performance or loan losses. Recall that results presented are consistent with bank 
holding companies operating as if external capital is more expensive than internally 
generated capital. To further examine this issue, I look at the relationship between loan 
growth at individual bank subsidiaries and internal additions to capital at both subsidiary 
and holding company levels. To the extent that either subsidiary or holding company 
additions to capital are positively related to loan growth (after controlling for the 
profitability of the holding company's lending opportunities), this provides additional 
evidence that bank holding companies are liquidity constrained. 

Additionally, examining this relationship may alleviate concerns that the observed 
correlation between internally generated capital and loan growth at the holding company 
level arises because internally generated capital proxies for the profitability of lending 
opportunities not captured by Tobin's Q. Indeed, a finding that subsidiary loan growth is 
related to internally generated capital at the holding company's other subsidiaries and in 
particular its non-bank subsidiaries would weaken the validity of this argument. In this 
regard, my tests are similar to Lamont (1993) who studied how a subsidiary's cash flows 
affected investment by an unrelated subsidiary within the same firm. 

Furthermore, in light of the evidence suggesting that bank holding companies are 
liquidity constrained, an interesting issue is how holding companies allocate capital among 
their subsidiaries. Stein (1995), following Williamson (1975), argues that capital market 
imperfections may give firms incentives to establish internal capital markets to allocate 



47 
resources more efficiently. Moreover, he speculates that firms with a narrow focus and 
hard to value assets may have greater incentives to create internal capital markets. A 
finding that subsidiary loan growth is more strongly related to holding company additions 
to capital than their own additions to capital would be consistent with bank holding 
companies operating internal capital markets and that banks are liquidity constrained. 

Table 9 presents regression results relating subsidiary loan growth to the same 
measures use to explain holding company loan growth in Table 3. One difference in this 
table is the inclusion of separate measures for the cash flows produced by the subsidiary 
bank and the rest of the holding company. I also use separate measures indicating 
capitalization of the subsidiary and the holding company. Regressions are performed 
using a between-effects regression which pools the observations for each subsidiary, using 
mean values of all variables. This controls for the autocorrelation in the residuals across 
the various years for each bank. I choose between-effects rather than fixed-effects due to 
the relatively short time period in which I have data (1985-1989). The sample contains 
over 2000 subsidiaries with at most 5 years of data per bank. Tests were also performed 
with OLS estimates (not reported) with qualitatively similar results. 

Results are presented for the full sample, the sample of banks whose assets 
represent less than 15 percent of their holding company's assets (bottom three size 
quartiles), and the sample of lead banks in each holding company (the largest subsidiary 
within the holding company). For the full sample and the small bank sample, loan growth 
at subsidiary banks is positively related to the holding company's market to book ratio (a 
proxy for loan opportunities). In addition, loan growth is positively related to the 



48 

Table 9 

Between effects regressions relating subsidiary loan growth to internal additions to capital, 

capital requirements, and subsidiary and bank holding company financial characteristics. 

The sample consists of 2339 subsidiaries of 215 multiple bank holding companies from 

1985-1989 (standard errors in parentheses) 



Dependent Variable = (Loans, - Loans,., ) / Loans,., 


Coefficient 


Overall 


Sample 


Small 


Bank 


Lead 


Bank 


(1) 


(2) 


(1) 


(2) 


(1) 


(2) 


(IAC H -IAC B )/(Loan H -Loan B ) a 


1.69** 
(0.184) 


1.65** 
(0.182) 


1.94** 
(0.219) 


1.90** 
(0.218) 


0.05 
(0.270) 


0.03 
(0.260) 


IAC B / Loan B 


0.29** 
(0.071) 


0.25** 
(0.069) 


0.26** 
(0.074) 


0.23** 
(0.071) 


1.86** 
(0.531) 


1 99** 
(0.509) 


(Surplus Capital / Assets) H 


-0.16 

(0.294) 




-0.35 
(0.33) 




0.58 
(0.774) 




(Surplus Capital / Assets) B 


-0.16 
(0.108) 




-0.17 
(0.11) 




1.25** 
(0.430) 




Bind H b 




-0.18** 
(0.025) 




-0.18** 
(0.026) 




-0.18** 
(0.064) 


Bind B 




0.03 
(0.019) 




0.03 
(0.020) 




-0.16* 
(0.082) 


Market / Book H 


0.50** 
(0.077) 


0.47** 
(0.077) 


0.52** 
(0.091) 


0.48** 
(0.091) 


0.30 
(0.181) 


0.27 
(0.178) 


(Securities / Assets) B 


0.03 
(0.03) 


0.02 
(0.03) 


0.02 
(0.03) 


0.01 
(0.027) 


0.09 
(0.101) 


-0.02 
(0.093) 


R 2 


0.097 


0.116 


0.096 


0.114 


0.125 


0.139 


N (Categories) 


6999 

(2339) 


6999 

(2339) 


6328 
(2162) 


6328 
(2162) 


762 
(278) 


762 
(278) 



a. IAC, = internal additions to capital (I=H for holding company and B for subsidiary) 

b. Bind, = 1 if bank capital ratio is less than or equal to the regulatory minimum. 
*, ** denote significance at the 5% and 1% levels, respectively 



49 
subsidiary's own internal additions to capital. However, loan growth is also significantly 
related to the additions to capital produced by all other firms within the holding company 
(measured by IAC H - IAC B ). For these samples the coefficient estimates on other 
subsidiaries' cash flow are nearly eight times that of the coefficient estimate on the bank's 
own cash flow. Furthermore, although it does not seem as if there is a strong link between 
surplus capital and loan growth, evidence suggests that subsidiaries are less likely to lend 
if their holding company (and not the subsidiary itself) is inadequately capitalized. 

Results for the lead bank sample differ substantially from the other samples. 
Specifically, the lead bank's own additions to capital are much more strongly correlated 
with loan growth than the holding company's additions to capital. Moreover, loan growth 
appears to be positively related to capitalization at the lead bank as indicated by the 
positive coefficient on surplus capital and negative coefficient on BIND for the lead bank. 
These results should not be surprising, given that the lead bank generates the majority of 
the loans, cash flows, and capital at the disposal of the holding company. In particular, the 
correlation between the cash flows of subsidiaries and the cash flows of the entire holding 
company is only 0. 10 for the full sample, yet 0.62 for the lead bank sample. 

To further investigate the relation between capitalization and loan growth, Table 
10 presents regressions for the full sample and the small bank sample relating loan growth 
to additions to capital and three measures for capital adequacy. Each measure is a dummy 
variable indicating whether the bank (holding company, subsidiary, or both) fails capital 
standards. Results are consistent with those presented in Table 9, and suggest that the 
capitalization of the holding company and not the subsidiary bank constrains loan growth. 



50 

Table 10 

Between effects regressions relating subsidiary loan growth to internal additions to capital, 

capital requirements, and subsidiary and holding company financial characteristics. The 

sample consists of 2339 subsidiaries of 215 multiple bank holding companies from 1985- 

1989 (standard errors in parentheses). 



Dependent Variable = (Loans, - Loans,., ) / Loans,., 


Coefficient 


Overall Sample 


Small Bank 


(1) 


(2) 


(3) 


(1) 


(2) 


(3) 


(IAGVIACByfLoanH-LoanB)" 


1.69** 
(0.182) 


1.63** 
(0.181) 


171** 
(0.184) 


1.94** 
(0.217) 


1.87** 
(0.216) 


1 95** 
(0.220) 


IAC B / Loan B 


0.29** 
(0.069) 


0.26** 
(0.069) 


0.26** 
(0.069) 


0.24** 
(0.071) 


0.23** 
(0.071) 


0.24** 
(0.072) 


Bind H =l andBind B =l b 


-0.70** 
(0.115) 






-0.77** 
(0.125) 






Bind H 




-0.18** 
(0.025) 






-0.18** 
(0.026) 




Bind B 






0.03 
(0.019) 






0.03 
(0.020) 


Market / Book H 


0.50** 
(0.077) 


0.47** 
(0.077) 


0.50** 
(0.078) 


0.52** 
(0.090) 


0.49** 
(0.090) 


0.52** 
(0.091) 


(Securities / Assets) B 


0.02 
(0.025) 


0.01 
(0.025) 


0.03 
(0.026) 


0.003 
(0.027) 


0.001 
(0.027) 


0.02 
(0.027) 


R 2 


0.11 


0.12 


0.10 


0.11 


0.12 


0.09 


N (Categories) 


7023 
(2339) 


7023 
(2339) 


7023 
(2339) 


6328 
(2162) 


6328 
(2162) 


6328 
(2162) 



a. IAC, = internal additions to capital (I=H for holding company and B for subsidiary) 

b. Bind, = 1 if bank capital ratio is less than or equal to the regulatory minimum. 
*, ** denote significance at the 5% and 1% levels, respectively 



51 
The results presented in Tables 9 and 10 provide support for the hypothesis that 
bank holding companies find external finance more costly than internally generated 
finance, and in response they establish an internal capital market. This interpretation 
follows from the observation that subsidiary loan growth is strongly related to holding 
company additions to capital. A competing explanation is that holding company cash 
flows proxy for investment opportunities at the subsidiary bank that are not captured by 
the holding company's market to book ratio or in the subsidiary's own additions to capital. 
To address this concern, I include loan growth at other subsidiaries, and cash flows of 
non-bank subsidiaries within the same holding company as explanatory variables. 

Table 1 1 documents results including the loan growth of the rest of the holding 
company as an additional variable to explain subsidiary loan growth. I still find that loan 
growth is positively related to additions to capital at both the holding company and 
subsidiary levels, and that the holding company effect remains considerably larger. 
Likewise, I still find that binding capital requirements matter at the holding company level, 
but not the subsidiary level. Surprisingly, the estimated coefficient on the holding 
company's loan growth is negatively related to subsidiary growth. Conceiving why a 
negative coefficient except in the context of an internal capital market in which holding 
companies allocate capital across competing uses is difficult. Overall, these results 
strongly affirm the conclusion that bank holding companies establish internal capital 
markets to allocate capital on a consolidated basis. 1 



The negative coefficient on other subsidiaries' growth is somewhat sensitive to 
sample and specification. If I exclude banks from Texas and Oklahoma (arguably the most 
constrained banks), the coefficient is positive, though not significantly different from zero 



52 

Table 1 1 

Between effects regressions relating subsidiary loan growth to internal additions to capital, 

loan growth in related subsidiaries, capital requirements, and subsidiary and holding 

company financial characteristics. The sample consists of 2339 subsidiaries of 215 

multiple bank holding companies from 1985-1989 (standard errors in parentheses). 



Dependent Variable = (Loans, - Loans,., ) / Loans,., 


Coefficient 


Overall Sample 


Small Bank 
Subsidiaries 


Lead Banks 


(IAC H -IAC B )/(Loan H -Loan B )" 


2.37** 
(0.296) 


2.46** 
(0.335) 


0.85 
(0.520) 


IAC B / Loan B 


0.33** 
(0.069) 


0.32** 
(0.071) 


2.07** 
(0.544) 


Bind H b 


-0.19** 
(0.026) 


-0.019** 
(0.028) 


-0.19** 
(0.068) 


Bind B 


0.03 
(0.020) 


0.03 
(0.021) 


-0.16* 
(0.086) 


Loan Growth H c 


-0.05* 
(0.026) 


-0.06* 
(0.029) 


-0.04 
(0.036) 


Market / Book H 


0.52** 
(0.082) 


0.059** 
(0.097) 


0.34 
(0.192) 


(Securities / Assets) B 


-0.03 
(0.027) 


-0.04 
(0.029) 


-0.04 
(0.099) 


R 2 


0.12 


0.12 


0.15 


N (Categories) 


6999 (2339) 


6328(2162) 


762 (278) 



a. IAC, = internal additions to capital (I=H for holding company and B for subsidiary) 

b. Bind, = 1 if bank capital ratio is less than or equal to the regulatory minimum. 

c. Loan Growth H equals loan growth of other subsidiaries in the holding company divided by their beginning of 
period loans outstanding. 

*, ** denote significance at the 5% and 1% levels, respectively 



53 
Table 12 presents results from the second robustness check, in which I replace the 
holding company's additions to capital with non-bank subsidiary's additions to capital. 
The results indicate that bank loan growth is positively related to the non-bank cash flows 
of the holding company, which provides further evidence that external capital is costly and 
banks operate internal capital markets. Moreover, the magnitude of this effect is similar to 
the magnitude of the holding company cash flows. Arguably, concluding that these results 
are spurious is harder, since it is less likely that non-bank subsidiary cash flows are 
positively related to lending opportunities of bank subsidiaries. In this regard, these tests 
provide the closest parallel to the experiment provided by Lamont (1993). 

As an additional test of the operation of an internal capital market, I examine the 
relation between the overall investment-cashflow sensitivity of the holding company and 
the subsidiary's dependence on both the holding company's and its own cash flows. The 
investment-cashflow sensitivity may estimate the magnitude of information asymmetries, 
although it is measured with error since it is an approximation using regression coefficients 
(see Table 6). To alleviate an errors in variables bias, I use the investment-cashflow 
sensitivity lagged one period as an instrumental variable. 

The severity of information asymmetries should be directly related to the growth of 
individual banks. Therefore, I expect subsidiary loan growth to be negatively related to 
the investment-cashflow sensitivity of the holding company. A finding that the importance 
of holding company cash flows is positively related to the holding company's investment- 
cashflow sensitivity would provide further evidence of the operation of an internal capital 
market. This indicates that the severity of the constraint faced by the holding company 



54 

Table 12 

Between effects regressions relating subsidiary loan growth to internal additions to capital, 

capital requirements, and subsidiary and holding company financial characteristics. The 

sample consists of 2339 subsidiaries of 215 multiple bank holding companies from 1985- 

1989 (standard errors in parentheses). 



Dependent Variable ■ (Loans, - Loans,., ) / Loans,., 


Coefficient 


Overall Sample 


Small Banks 


Lead Bank 


(Non-Bank IAC)/(Loan H -Loan B ) a 


0.56** 
(0.173) 


1.28** 
(0.279) 


0.09 
(0.203) 


IAC B / Loan B 


0.33** 
(0.069) 


0.28** 
(0.072) 


1.98** 
(0.506) 


Bind H b 


-0.19** 
(0.025) 


-0.19** 
(0.026) 


-0.18** 
(0.064) 


Bind B 


0.01 
(0.019) 


0.02 
(0.020) 


-0.16* 
(0.082) 


Market / Book H 


0.66** 
(0.075) 


0.69** 
(0.087) 


0.28 
(0.177) 


(Securities / Assets) B 


0.05* 
(0.026) 


0.05 
(0.027) 


-0.02 
(0.093) 


R 2 


0.09 


0.09 


0.14 


N (Categories) 


6999 (2339) 


6328(2162) 


762 (278) 



a. IAC, = internal additions to capital (I=H for holding company and B for subsidiary) 

b. Bind, = 1 if bank capital ratio is less than or equal to the regulatory minimum. 
*, ** denote significance at the 5% and 1% levels, respectively 



55 
directly influences the subsidiary's dependence on holding company earnings. Table 13 
presents between effects regressions including the holding company's investment-cashflow 
sensitivity and two interaction variables designed to test the relation between this 
sensitivity and subsidiary reliance on both its own and holding company cashflows. These 
variables are the interactions between holding company investment-cashflow sensitivity (as 
estimated from equation (1) Table 5) and the two cash flow measures used above. 2 

At first glance, results in Table 13 might appear to be confusing. In particular, the 
negative and significant coefficient on the holding company's cash flows for both the 
overall sample and the lead banks may initially cause some concern. However, consider 
that this variable appears twice in the regression, the second time interacted with the 
holding company's investment-cashflow sensitivity. This sensitivity averages just under 4 
(recall from Table 6), and for the majority of banks lies in a range from 3 to 5. After 
combining these two estimates, it becomes clear that the total effect of holding company 
cash flows will be positive for virtually all banks. Moreover, the positive coefficient on 
the interaction term indicates that the severity of the holding company's constraint directly 
affects the subsidiary's dependence on holding company earnings. Specifically, as holding 
companies become more cash flow constrained, subsidiaries become more reliant on 
holding company earnings. Likewise, the negative and significant coefficient on the 
holding company's sensitivity (for the overall sample and small banks) indicates that as 
holding company's become more constrained, their subsidiaries invest less. These results 
provide additional evidence that holding companies operate internal capital markets. 



Results are similar if the sensitivities are estimated from regressions in Table 4. 



56 

Table 13 

Between effects regressions relating subsidiary loan growth to internal additions to capital, 

estimated investment-cashflow sensitivity, capital requirements, and subsidiary and holding 

company financial characteristics. The sample consists of 2339 subsidiaries of 215 

multiple bank holding companies from 1985-1989 (standard errors in parentheses). 



Dependent Variable = (Loans, - Loans,., ) / Loans,., 


Coefficient 


Overall Sample 


Small Banks 


Lead Bank 


(IAC H -IAC B )/(Loan H -Loan B ) , ' 


-1.984** 
(2.052) 


-0.837 
(2.571) 


-10.60* 
(4.276) 


IAC B / Loan B 


0.616 
(1.328) 


0.169 

(1.513) 


11.87* 
(6.56) 


Bmd H b 


-0.145** 
(0.022) 


-0.159** 
(0.023) 


-0.193 ** 
(0.069) 


Bind B 


0.026 
(0.017) 


0.031 
(0.019) 


0.177* 
(0.087) 


Market / Book H 


0.344 ** 
(0.068) 


0.468 ** 
(0.089) 


0.221 
(0.197) 


(Securities / Assets) B 


0.032 
(0.026) 


0.007 
(0.029) 


-0.063 
(0.115) 


Holding Company Investment- 
Cashflow Sensitivity ,., 


-0.038 ** 
(0.023) 


-0.033 * 
(0.013) 


0.002 
(0.044) 


(IAC H -IAC B )/(Loan H -Loan B ) d * 
Holding Company Investment- 
Cashflow Sensitivity ,., 


1.059* 
(0.532) 


0.742 
(0.658) 


2.997 * 
(1.214) 


IAC B / Loan B * Holding Company 
Investment-Cashflow 
Sensitivity ,., 


-0.103 
(0.332) 


0.012 
(0.378) 


-2.448 
(1.652) 


R 2 


0.155 


0.136 


0.169 


N (Categories) 


6785 (2305) 


6186(2143) 


751 (274) 



a. IAC, - internal additions to capital (I=H for holding company and B for subsidiary) 

b. Bind, = 1 if bank capital ratio is less than or equal to the regulatory minimum. 

c. Loan Growth H equals loan growth of other subsidiaries in the holding company divided by their beginning of 
period loans outstanding. 

d. Holding Company Investment-Cashflow Sensitivity is estimated from coefficients on internal additions to 
capital and interaction variables from regression (1) in Table 5. To alleviate errors-in variables bias, I use the 
lag investment-cashflow sensitivity as an instrumental variable. 

*, ** denote significance at the 5% and 1% levels, respectively 



CHAPTER 6 
EXTERNAL CAPITAL ISSUANCE 

The above analysis is consistent with the hypothesis that capital market frictions tie 
investment to earnings for banks. To further study this issue, this chapter examines the 
severity of information asymmetries surrounding external capital issuances. Specifically, if 
the magnitude of the investment-cashflow sensitivity proxies for the severity of 
information asymmetries, then ceteris paribus the likelihood that banks issue external 
capital should be negatively related to this sensitivity. In addition, this sensitivity may 
also be related to the expected costs associated with a security issuance. Banks that face 
larger information asymmetries may expect higher underwriting fees and more negative 
abnormal stock returns associated with an external capital issuance than banks that face 
smaller information asymmetries. 

Table 14 describes a summary of 461 security issuances by 157 different bank 
holding companies from 1982-1994. The timing of security issuances suggests that 
increases in capital standards may have induced banks to raise external funds in order to 
replenish surplus capital. Notice that the most active issuance years (1985-1987, and 
1991-1993) follow increases in capital standards. 

Table 14 also documents the average abnormal returns for the security issuances in 
my sample. I find that the average abnormal return following the announcement of a 
common stock issuance is just less than -1%. Moreover, capital deficient banks 

57 



58 

Table 14 
Summary of bank holding company security issuances from 1982-1994 


year 


common stock 


preferred stock 


subordinated 
notes 


total 




1982 


1 


10 


4 


15 


1983 


4 


19 


4 


27 


1984 


9 


8 


17 


34 


1985 


19 


6 


26 


51 


1986 


28 


4 


16 


48 


1987 


7 


8 


35 


50 


1988 


1 


4 


9 


14 


1989 


4 


6 


15 


25 


1990 


2 


4 


4 


10 


1991 


16 


16 


18 


50 


1992 


22 


18 


36 


76 


1993 


9 


6 


25 


40 


1994 





5 


16 


31 


total 


122 


114 


225 


461 


Mean Offer Size (millions) 


95,451 


123,128 


135,393 


124,810 


Mean (Offer Size / Assets) 


1.0% 


0.6% 


1.1% 


0.9% 


Mean Underwriter Fees 


4.2% 


2.8% 


1.4% 


2.7% 


Mean Abnormal Return 
full sample 


-1.32% 
(z=-5.6,N=105) 


0.15% 
(z=0.3, N=98) 


-0.19% 
(z=-0.7,N=158) 


-0.42% 
(z=-3.5,N=361) 


Mean Abnormal Return 
ifbind=0 


-1.49% 
(z=-6.4, N=85) 


-0.02% 
(z=-0.1,N=74) 


-0.16% 
(z=-0.5,N=144) 


-0.48% 
(z=-3.5, N=303) 


Mean Abnormal Return 
ifbind=l 


0.37% 
(z=0.1,N=20) 


0.05% 
(z=0.7, N=24) 


-0.05% 
(z=-0.7,N=14) 


-0.12% 
(z=-0.8, N=58) 


Test Statistic of Difference 
in Mean Abnormal 
Returns, by bind 


z=1.50 


z=0.39 


z=1.15 


z=0.86 


Security issuances collected frc 
Announcement dates collected 


m the Investment D 
from Dow Jones Ne 


salers Digest, 
ws Retrieval 




1 





59 
experience approximately zero abnormal return, while adequately capitalized banks lose 
approximately 1.5% in value. This is consistent with Cornett and Tehranian (1994), and 
provides evidence that the market anticipates external equity issues by inadequately 
capitalized banks. Also consistent with previous studies, I find that preferred stock and 
subordinated note issues do not invoke significant abnormal returns. This may occur 
because these securities are less informationally intensive than common stock, so an 
issuance of these securities may not elicit as severe of a lemon's problem. 1 

A bank's decision of whether to issue is likely to be related to the information 
asymmetries it faces. Therefore, I develop a logit model which predicts the choice to issue 
based on firm and market characteristics. Following Bayless and Chaplinsky (1991) 
certain factors can be identified which are likely to influence the decision to issue. It can 
be shown that an increase in the firm's stock price increases the share of returns to an 
investment project retained by old stockholders and reduces the loss of existing firm value 
to new stockholders. Thus, I include the ratio of the last three months' average stock 
price to the prior thirty-six months' average. In addition, prior studies find that the 
aggregate market conditions at the time of issuance have a significant influence on offer 
choice. Essentially, firms are more likely to issue equity following strong equity market 
performance. To control for market conditions, I include the ratio of the three-month 
average market price (CRSP equal weighted index) to the thirty-six month average. The 
variable Risk, the standard deviation of the firm's common stock returns, controls for 
stock volatility. 



1 See Mikkelson and Partch (1986) 



60 
In previous chapters, I argue that capital requirements affect bank decision making 

by placing a binding constraint on the utilization of debt funds. This suggests that banks 

which are capital deficient may be more likely to issue external funds. To control for this 

possibility, I include a dummy variable for whether banks fail capital requirements, Bind, 

as an explanatory variable. A second implication of this paper is that securities holdings 

may provide banks with significant financial slack, especially if regulators enforce 

leverage-based capital standards. In particular, firms with sufficient resources allocated to 

securities holdings can fund growth through the liquidation of these holdings. As a result, 

firms with a large buffer stock of securities may be less likely to issue external funds. 

Thus, I include the ratio of securities to assets as an explanatory variable. 

In the Myers and Majluf (1984) model, an increase in financial slack increases the 
costs of adverse selection. Therefore, and increase in slack reduces the likelihood of an 
equity offering. As an additional proxy for slack, I include a variable called free cash flow 
(see Bayless and Chaplinsky (1996)). Free cash flow is designed to measure the flow of 
funds constraint which motivates firms to issue securities when positive new present value 
projects cannot be financed internally. Free cash flow is defined as current net income 
less dividends and loan growth (investment). Banks are expected to be more likely to 
issue when they have less free cash flow, hence I expect a negative coefficient. 

This paper maintains that banks are concerned with the amount of regulatory 
capital that they generate internally. Presumably, banks would fund all growth through 
internally generated additions to capital if possible. However, that a bank chooses to issue 
external funds does not necessarily mean that it requires a capital injection from a 



61 
regulatory point of view. It could be that sufficient profitable lending opportunities exist 
that the bank could not take advantage of without raising external capital. Either way, the 
amount of capital generated internally is likely to be an important factor in the decision to 
issue external funds. To capture this relationship, I include the additions to capital, 
lagged one observation, as an explanatory variable. This variable indicates the amount of 
regulatory capital generated in the previous year. A negative coefficient on additions to 
capital indicates that banks are more likely to issue if they have not been generating 
sufficient capital internally. On the other hand, a positive coefficient indicates that banks 
are more likely to issue when they have profitable growth opportunities. 

Optimal capital structure theory maintains that firms have target debt ratios. 
Because the costs of debt exceed the benefits for debt ratios above the target, firms are 
predicted to be more likely to issue the further the firm's current debt ratio is above the 
target ratio. Banks' optimal capital structure is likely to depend on the current capital 
requirements. Indeed, the previous chapters provide evidence that surplus capital is an 
important determinant of bank growth. I approximate each bank's optimal capital 
structure as its average surplus capital over the entire sample period (1982-1994). 2 The 
deviation from the optimal, designated Target, is then calculated as the difference between 
this average and the bank's current period surplus capital. A positive value for Target 
indicates that the bank has less surplus capital than optimal. Since all security issues in my 
sample augment regulatory capital, I expect a positive coefficient on Target. 



This definition may not be completely accurate, since the optimal surplus capital 
may change as capital standards change. As a separate test, I calculate Target over each 
regime. Results are similar. 



62 
In a recent study, Bayless and Chaplinsky (1996) find that firms are more likely to 
issue equity in a 'hot' issue market. Drawing on this research, I identify hot issuance 
markets, and create an appropriate dummy variable (Hot) to include as an explanatory 
variable. To identify hot markets, I use aggregate equity issue volume data from the 
Federal Reserve System's Annual Statistical Digest. I classify the periods using scaled 
issue volume, which is monthly issue volume divided by the month end value of 
outstanding equity from the CRSP and NASD tapes. 3 I rank three-month moving 
averages of equity issue volume into quartiles. Hot markets are identified as at least three 
contiguous months where equity volume exceeds the upper quartile. 

The main purpose of this analysis is to examine the relation between information 
asymmetries and the likelihood of issuance. If the predicted investment-cashflow 
sensitivity proxies for the severity of capital market frictions, it should be negatively 
related to the probability of issuance. The investment-cashflow sensitivity is estimated 
using regression (1) from Table 5. 4 Specifically, the coefficients on additions to capital 
and the interaction variables are combined to predict the sensitivity for each bank in every 
year (see Table 6). 

Two potential problems arise when including this sensitivity as an explanatory 
variable. First, since it is estimated using regression coefficients, it is measured with error. 
To alleviate this problem, I instrument for this sensitivity using a lagged observation. 



5 Like Bayless and Chaplinsky (1996), results are not sensitive to the use of scaled 
volume. If I classify based on nominal dollar or real dollar volume, results are similar. 

Results are similar if the investment-cashflow sensitivities are estimated from 
regressions in Table 4. 



63 
Second, there may be a causality problem. Banks that issue securities may be less cash 
flow constrained not because of information costs but because they raised external capital. 
However, it is less likely that banks that issue were also less constrained by cash flow in 
the previous year because of the decision to raise funds. Again this can be alleviated by 
using the investment-cashflow sensitivity lagged one year. 

Table 1 5 presents descriptive statistics based on whether the bank issues in a given 
year, and if so which type of security it issues. Recall from Table 7 that the investment- 
cashflow sensitivities are negatively related to bank size. This is consistent with large 
banks facing less severe information asymmetries than small banks. Thus it should not be 
surprising that banks which issue are significantly larger than banks which do not issue. 
The average size for non-issuers is just over six billion, while stock issuers average over 
twenty billion. Also, issuers are increasing loans faster and generating more internal 
capital (except for preferred stock issuers) than non-issuers. However, issuers also have 
significantly less free cash flow. These results are consistent with firms issuing when they 
need funds to implement positive net present value projects. 

This chapter is interested in examining the relation between the investment- 
cashflow sensitivities and the likelihood of security issuance. One implication of capital 
market frictions is that firms with more severe information asymmetries will be less likely 
to issue external funds. Perhaps surprisingly, non-issuers have significantly lower 
investment-cashflow sensitivities than issuers. However, this is likely influenced by the 
fact that issuers have significantly less financial slack as measured by surplus capital and 
securities holdings, and are more likely to be inadequately capitalized. To further address 



Table 15 

Descriptive statistics (means, with medians in parentheses) for 289 bank holding 

companies classified by type of security issuance. 3 



64 



Variable 


no issuance 


common stock 
issuance 


preferred stock 
issuance 


subordinated 
note issuance 


Total Assets (millions) 


6,533 
(2,276) 


20,100 * 
(5,597) * 


51,300* 
(32,300) * 


38,600 * 
(22,800) * 


Loan Growth b 


0.061 
(0.076) 


0.191* 
(0.151)* 


0.087 
(0.055) 


0.152* 
(0.116)* 


Internal Additions to 
Capital/ Loans,., 


0.014 
(0.017) 


0.019* 
(0.019)* 


0.015 
(0.014) 


0.019* 
(0018) 


Market / Book Assets' 1 


1.005 
(0.999) 


1.004 
(0.996) 


0.991 * 
(0.989) * 


1.006 
(1.000) 


Book Capital in Excess 
of Requirement / Assets e 


0.025 
(0.021) 


0.017* 
(0.014)* 


0.017 * 
(0.010) * 


0.023 
(0.017) * 


Securities / Assets 


0.215 
(0.208) 


0.193 * 
(0.195) 


0.134* 
(0.119)* 


0.165* 
(0.159)* 


Risk f 


0.023 
(0.018) 


0.022 
(0.017 


0.023 
(0.018) 


0.019 
(0.016) 


Predicted Investment- 
Cashflow Sensitivity*,., 


3.688 
(3.758) 


3.915* 
(3.915)* 


4.072 * 
(4.174)* 


3.903 * 
(4.006) * 


Free Cash Flow/Loans,., h 


-0.055 
(-0.066) 


-0.185* 
(-0.145)* 


-0.082 * 
(-0.048) 


-0.144* 
(-0.110)* 


Percentage with Capital 
less than requirement. 


4.55% 


9.02% * 


21.9%* 


9.78% * 


Number of Observations 


1954 


122 


114 


225 



a. Data are from the Federal Reserve Y-9 tape. 

b. Loan growth equals change in total loans outstanding divided by loans outstanding at time t- 1 . 

c. Internal additions to capital equals net income plus changes in loan loss provisions (up to regulatory 
maximum). 

d. Market to book value of assets equals (Total Assets - Book Equity + Market Equity) / Total Assets. Market 
Equity equals the market value of common equity from CRSP. The ratio is calculated at year end for the prior 
year. 

e. Book capital in excess of requirement equals the bank's book capital for regulatory minimum Tier II capital 
ratio. Tier II capital equals common stock, preferred stock, plus eligible subordinated debt and loan loss 
reserves. For the period 1 982- 1 984 the requirement is 5.5% of total assets. For 1 985- 1 989 the requirement is 
6%. Beginning m 1 990, the requirement is based on risk-weighted assets. For 1 990- 1 99 1 , the minimum is 
7.25% of risk- weighted assets, while from 1 992- 1 994 the minimum is 8%. 

f. Risk equals the standard deviation of the firm's daily stock return, after adjusting for bid-ask bounce 

g. Investment-Cashflow Sensitivity is estimated using coefficients on internal additions to capital and 
interaction variables from regression ( 1 ) in Table 5. 

h. Free Cash Flow is net income less dividends and loan growth. 

* denotes significantly different from the no investment sample at better than the 5% level. 



65 
this issue, I estimate probit regression models of security choice while controlling for the 
investment-cashflow sensitivity, surplus capital, and securities holdings. 5 

The sample contains a pooled time-series cross section of data. As a result, 
observations may not be independent, especially for the common stock issuance model. In 
particular, if a bank issues common stock in any given year, it is likely to not issue again in 
the next year. In fact, for only twenty out of one hundred and twenty-two issues did a 
bank issue common stock in consecutive years. Likewise, forty-two out of one hundred 
and fourteen preferred stock, and sixty-eight out of two hundred and twenty-five 
subordinated note issues occurred from a bank in consecutive years. To address this 
problem, I include a dummy variable indicating whether the bank issued in the previous 
year. 6 Specifically, I create four dummy variables (any security, common stock, preferred 
stock, and subordinated note) to include in the appropriate regressions, and expect the 
coefficients to be negative. 

Table 16 presents the results from probit models which estimate the decision to 
issue based on the aforementioned firm and market characteristics. Because the 
investment-cashflow sensitivity is related to capitalization and securities holdings, I 
estimate the regressions both with and without this variable. Regardless of security type, 



5 Results are similar using logit regressions. 

5 As a separate test, I estimate the probit models for each year independently. In 
these regressions, the coefficient estimates were relatively stable for the any issuance, 
preferred stock, and subordinated note models. However, for the common stock model, 
coefficients were not as stable. Moreover, in all models, coefficient estimates were not as 
significant as those presented in Table 15, perhaps due to the use of many fewer 
observations. 



66 



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67 
inclusion of the investment-cashflow sensitivity increases the pseudo R squared of the 
model (and log likelihood ratio). Moreover, in three of four models after controlling for 
capitalization and securities holdings, I find a negative and significant relation between the 
choice of issuance and the investment-cashflow sensitivity. This provides evidence that 
investment-cashflow sensitivities proxy for the severity of information asymmetries. 

Consistent with the hypothesis that capital requirements impose binding 
constraints, I find that the probability of issuing external funds is greater for banks that fail 
capital requirements. Specifically, for the any security, common stock, and preferred 
stock models, coefficient estimates on Bind, are positive and significant after controlling 
for the investment-cashflow sensitivity. Moreover, the negative coefficients on securities 
indicate that banks with more securities holdings are less likely to raise external capital. 
This provides further evidence that banks rely on buffer stocks of capital and securities to 
fund growth during a liquidity crisis. 

The coefficient estimates on the dummy variable for issuance in the previous year 
are negative and statistically significant for all four issuance models. This supports the 
notion that banks are unlikely to issue external capital securities in consecutive years. 
Also, the negative coefficients on free cash flow indicate that banks are more likely to 
issue capital when they need funds to support growth. 

As a second test of the relation between information costs and external capital 
issuances, I examine the relation between investment-cashflow sensitivities and banks' 
anticipated costs of security issuance. Following Calomiris and Himmelberg (1995), I 
estimate expected underwriting costs based on firm characteristics and sort firms into high 



68 
and low cost categories. Using these categories, I determine whether high cost firms 
display greater investment-cashflow sensitivities than low cost firms. Calomiris and 
Himmelberg identify certain characteristics which are important in determining 
underwriting fees. I use similar bank characteristics to estimate the fee model. 

In Calomiris and Himmelberg, financial working capital, leverage, and sales are the 
most important characteristics. I estimate financial working capital as securities holdings, 
and control for leverage with capitalization. Translating sales to a banking firm 
characteristic, I choose internally generated additions to capital. I pick additions to capital 
over income because capital requirements cause banks to be concerned with the amount of 
regulatory capital that they generate. I also include free cash flow to capture the flow of 
funds constraint that motivates banks to issue. In addition, I include size, the deviation 
from optimal capital structure (Target), and the volatility of stock returns (Risk). 7 

As in Calomiris and Himmelberg, this is not intended to be a structural model. The 
process of experimentation that yields the model was an search for a model that 
maximized adjusted R squared. Because of this problem, I choose not to focus on 
individual coefficient estimates, rather I am more concerned with the accuracy of 
predictions based on this model (the correlation between actual fees and predicted fees for 
common stock issuances is more than 0.8). Moreover, I will sort firms into categories 
based on this prediction so as not to rely on the prediction itself, but only a dummy 
variable which indicates whether the prediction is over or under the median prediction. 



1 I experiment with a number of alternative specifications, but report only the one 
which yielded the largest adjusted R squared. 



69 
Table 17 presents results from a heteroskedastic consistent regression relating the 
underwriting fees to firm characteristics. The most important firm characteristics in 
determining fees are size and the amount of internal capital generation. Also, the adjusted 
R squared for these models are similar to those from Calomiris and Himmelberg. 

Because I am interested in using information about issuers to estimate the external 
financing costs of non-issuers, I correct for potential selectivity bias before applying the 
model to construct expected underwriting costs for issuers and non-issuers. That is, the 
decision to issue is not random, and that decision is likely to be correlated with some or all 
of the regressors in the underwriting fee model. To correct for this problem, I use a two- 
step Heckman procedure in which the decision to issue is modeled as a probit model. The 
probability of issuing derived from this probit enters as an explanatory variable in the 
underwriting fee model. Since a probit model has been specified in Table 16, 1 rely on this 
model for the Heckman procedure. Because my goal is to use predictors from the 
Heckman procedure to explain differences in investment-cashflow sensitivities, I use the 
probit model without the investment-cashflow sensitivity as an explanatory variable. 

The results from the underwriting fee model and the probit model after correcting 
for selectivity bias are presented in Table 18. The coefficients from the underwriting fee 
model are used to construct predicted values of the cost of issuing each type of security 
for all firms. I then create a dummy variable (High Fees) which equals one if the predicted 
fees are above the median predicted fees, or zero otherwise for each security type. This 
dummy variable is employed to estimate the relation between expected issue costs and the 
sensitivity to internally generated funds. 



70 

Table 17 

Heteroskedastic consistent regressions relating total underwriting expense to firm 

characteristics. Year dummy variables included (results not reported). The sample 

consists of 289 bank holding companies from 1982-1994 (standard errors in parentheses). 



Dependent Variable= percentage fees associated with: 


Variable 


Common Stock 


Preferred Stock 


Subordinated Notes 


Bind" 


-0.001 
(0.002) 


0.002 
(0.002) 


-0.001 
(0.003) 


Log (Total Assets,.,) 


-0.007 ** 
(0.001) 


-0.006 ** 

(0.001) 


-0.006 ** 
(0.002) 


Free Cash Flow / Loans,., b 


-0.001 
(0.005) 


0.002 
(0.003) 


-0.005 
(0.014) 


Lag (Additions to Capital / 
Loans,.,) 


-0.147 
(0.084) 


-0.189* 
(0.085) 


-0.389 * 
(0.177) 


Securities / Assets,., 


0.025 * 
(0.013) 


-0.016 
(0.018) 


0.001 
(0.024) 


Target 


-0.085 
(0.076) 


-0.069 
(0.042) 


0.092 
(0.095) 


Risk d 


0.748 ** 
(0.247) 


0.426 ** 
(0.152) 


0.432 
(0.523) 


Risk 2 


-4.635 ** 
(1.777) 


-2.075 
(0.763) 


-3.697 
(8.207) 


N (Adjusted R 2 ) 


109 (0.661) 


95 (0.419) 


116 (0.417) 



a. Bind =1 if surplus capital is less than or equal to zero, =0 otherwise 

b. Free Cash Flow= net income less dividends and investment. 

c. Target = the bank's average surplus capital over the entire sample period minus it's actual surplus capital. 

d. Risk= standard deviation of daily stock return 

*, ** denote significance at the 5% and 1% levels, respectively 



71 

Table 18 

Regression models relating underwriting fees to firm characteristics, correcting for selectivity bias 

using Heckman's two step procedure, (standard errors in parentheses) 





common 


stock 


preferred 


stock 


subordinated 


notes 


Variable 


Probit Model 
(l=issuer) 


% fee 


Probit Model 
(l=issuer) 


% fee 


Probit Model 
(l=issuer) 


% fee 


Bind" 


0.03 
(0.067) 


0.01 
(0.01) 


-0.06 
(0.143) 


0.002 
(0.003) 


0.28* 
(0.138) 


0.002 
(0.003) 


Log (Total Assets,.,) 


0.11 ** 
(0.018) 


-0.01 ** 
(0.001) 


0.33 ** 
(0.021) 


-0.01 ** 
(0.001) 


0.79** 
(0.022) 


-0.01 ** 
(0.001) 


Free Cash Flow / 
Loans,_, b 


-2.08 ** 
(0.117) 


-0.002 
(0.005) 


-1 ]9 ** 
(0.114) 


0.002 
(0.008) 


-1.21 ** 
(0.116) 


-0.01 
(0.006) 


Lag (Additions to 
Capital / Loans,.,) 


9.63 ** 
(2.062) 


-0.17 
(0.106) 


-5.27 ** 
(2.167) 


-0.19 
(0.109) 


37.2** 
(2.148) 


-0.28 
(0.176) 


Securities / Assets,., 


-9.14 ** 
(0.332) 


0.02 
(0.017) 


-2.50 ** 
(0.319) 


-0.01 
(0.024) 


-10.8** 
(0.336) 


-0.03 
(0.024) 


Target' 


54.3 ** 
(2.126) 


-0.08 
(0.083) 


j J 7 ** 
(1.945) 


-0.08 
(0.122) 


21.2** 
(2.084) 


0.19 
(0.113) 


Risk d 


-3.22 * 
(1.415) 


0.87 ** 
(0.271) 


-8.73 ** 
(2.062) 


0.42* 
(0.25) 


-0.71 
(1.475) 


0.20 
(0.504) 


3 month avg Stock 
Price / 36 month avg 


5.68 ** 
(0.289) 




6.25 ** 
(0.287) 




15.1 ** 
(0.797) 




3 month avg Market 
Price / 36 mo avg 


-35.3 ** 
(1.979) 




0.71 
(2.089) 




-22.9 ** 
(2.072) 




Hot 


0.28 ** 
(0.055) 




0.25 ** 
(0.059) 




-0.59** 
(0.057) 




Issued in the Previous 
Year =1 if yes, Oifno. 


-0.42 ** 
(0.103) 




-0.35 ** 
(0.112) 




0.01 
(0.095) 




Inverse Mills Ratio 
from Probit" 




0.003 ** 
(0.0002) 




-0.002 
(0.0135) 




0.01 ** 
(0.002) 



a. Bind -1 if surplus capital is less than or equal to zero, =0 otherwise 

b. Free Cash Flow= net income less dividends and investment. 

c. Target = the bank's average surplus capital over the entire sample period minus it's actual surplus capital. 

d. Risk= standard deviation of daily stock return 

e. Inverse Mills Ratio = the probability of issuance derived from the Probit model 
*, ** denote significance at the 5% and 1% levels, respectively 



72 
Table 19 presents fixed-effects regressions of loan growth identical to the model from 
Table 3 with one important difference. I include the interaction of the variable High Fees with 
additions to capital. The three categories of regressions indicate the security type for which the 
underwriting fees are predicted. Because of a potential simultaneity bias induced by estimating 
fees and then using the estimation as an explanatory variable, I instrument for this variable with a 
lagged observation of High Fees. This interaction term is designed to test the hypothesis that 
firms which anticipate larger external finance costs are more constrained by internally generated 
funds. Regardless of security type, banks which anticipate higher than median underwriting fees 
are more sensitive to internally generated funds. 8 In other words, expected external finance costs 
affect a bank's reliance on internally generated funds. This finding provides evidence that the 
magnitude of the investment-cashflow sensitivity proxies for the size of the wedge between 
internal and external financing costs. 

Continuing along these lines, the expected abnormal returns following the announcement 
of a security issuance may proxy for expected costs of issuance, and therefore may be related to 
the investment-cashflow sensitivities. Using the same specifications from the underwriting fees 
model, I estimate the abnormal stock returns based on firm characteristics using weighted least 
squares, weighing each observation by the standard error from a market model regression. Table 
20 presents results that indicate that abnormal returns are difficult to predict with observable 
characteristics, as the adjusted R squared from these models is much lower than from the 
underwriting fee models. However, this problem should simply introduce more noise in the 



1 In additional tests, I divided firms into quartiles based on expected financing 
costs. In these tests I find a significant difference between the highest and lowest quartile. 
I also find a significant difference between the top two quartiles. 



73 



Table 19 

Fixed effects regressions relating loan growth to internal additions to capital, expected 

underwriting fees, and firm financial characteristics. The sample consists of 289 bank 

holding companies from 1982-1994 (standard errors in parentheses). 



Dependent Variable = (Loans 


, - Loans,., ) / Loans,., 










Variable 


common 


stock 


preferred 


stock 


subord. 


notes 


Additions to Capital / 
Loans,., 


4.67 ** 
(0.231) 


3.59** 
(0.188) 


4.66 ** 
(0.234) 


3.76** 
(0.201) 


4.45 ** 
(0.242) 


3.65 ** 
(0.202) 


High Fees,., * Additions to 
Capital /Loans,.," 


0.38* 
(0.186) 


0.39* 
(0.184) 


0.34* 
(0.179) 


0.39* 
(0.177) 


0.82 ** 
(0.165) 


0.93 ** 
(0.216) 


Surplus Capital / Assets,., 


0.93 ** 
(0.162) 




0.91 ** 
(0.164) 




0.82 ** 
(0.165) 




Surplus Capital *Additions 
to Capital / Loans,., 


-30.7 ** 
(4.588) 




-30.4 ** 
(4.615) 




-26.6 ** 
(4.761) 




Bind b 




-0.05 * 
(0.009) 




-0.05 ** 
(0.009) 




-0.05 ** 
(0.009) 


Bind * Additions to Capital 
/ Loans,., 




0.46 

(0.459) 




0.99* 
(0.512) 




0.71 
(0.514) 


Securities / Assets,., 


0.13 ** 
(0.039) 


0.15** 
(0.039) 


0.13 ** 
(0.040) 


0.13** 
(0.040) 


0.13** 
(0.040) 


0.13 ** 
(0.039) 


Market / Book Assets,., 


0.26 ** 
(0.048) 


0.27 ** 
(0.049) 


0.27 ** 
(0.048) 


0.26 ** 
(0.049) 


0.25 ** 
(0.048) 


0.24 ** 
(0.048) 


log (Assets,.,) 


-0.07 ** 
(0.005) 


-0.07 ** 
(0.005) 


-0.07 ** 
(0.006) 


-0.07 ** 
(0.005) 


-0.07 ** 
(0.005) 


-0.07 ** 
(0.005) 


Lag loan growth 


0.07 ** 
(0.010) 


0.07 ** 
(0.010) 


0.07 ** 
(0.010) 


0.07 ** 
(0.010) 


0.05 ** 
(0.011) 


0.04 ** 
(0.012) 


R 2 


0.379 


0.377 


0.379 


0.375 


0.383 


0.379 


N (categories) 


1986 
(289) 


1986 
(289) 


1986 
(289) 


1986 
(289) 


1986 
(289) 


1986 
(289) 


F statistic, Bank dummies 


2.33 ** 


2.62 ** 


2.33 ** 


2.60 ** 


2.37 ** 


2.65 ** 



a. High Fees =1 if the firms predicted fees from the Underwriting Fees model in Table 18 (corrected for 
selectivity bias) are greater than the median predicted fees, =0 otherwise. 

b. Bind=l ifsurpluscapital<=0, otherwise. 

*, ** denote significance at the 5% and 1% levels, respectively 



74 



Table 20 

Weighted least squares regressions relating abnormal stock returns following the 

announcement of a security issuance to firm characteristics. Observations are weighted 

by the standard errors from a market model regression. Year dummy variables included 

(results not reported). The sample consists of 289 bank holding companies from 1982- 

1994 (standard errors in parentheses). 



Dependent Variable= abnormal stock returns associated with: 


Variable 


Common Stock 


Preferred Stock 


Subordinated Notes 


Bind 3 


0.03 ** 
(0.012) 


-0.01 
(0.011) 


-0.01 
(0.001) 


Log (Total Assets,.,) 


0.001 
(0.002) 


0.004 
(0.004) 


0.002 
(0.002) 


Free Cash Flow / Loans,.| b 


-0.03 
(0.023) 


0.03 * 
(0.013) 


0.02 
(0.011) 


Lag (Additions to Capital / 
Loans,.,) 


-0.31 
(0.457) 


-0.17 
(0.366) 


0.32 
(0.233) 


Securities / Assets,., 


-0.01 
(0.065) 


0.02 
(0.077) 


0.01 
(0.031) 


Target' 


-0.08 
(0.377) 


-0.17 
(0.366) 


0.08 
(0.193) 


Risk d 


-0.76 
(0.802) 


0.06 

(0.637) 


-1.15 
(0.872) 


Risk 2 


6.18 
(5.972) 


1.06 
(3.121) 


12.9 
(12.07) 


N (Adjusted R 2 ) 


107(0.166) 


90 (0.339) 


155(0.158) 



a. Bind - 1 if surplus capital is less than or equal to zero, =0 otherwise 

b. Free Cash Flow= net income less dividends and investment. 

c. Target = the bank's average surplus capital over the entire sample period minus it's actual surplus capital. 

d. Risk= standard deviation of daily stock return 

*, ** denote significance at the 5% and 1% levels, respectively 



75 
estimates and bias against finding any relation between expected costs and investment- 
cashflow sensitivities. 

Table 21 presents results from the probit and abnormal return models using the 
Heckman procedure correcting for selectivity bias. As before, the coefficients from the 
abnormal return model are used to construct predicted values of the cost of issuing each 
type of security for all firms. I then create a dummy variable (Large Abnormal Returns) 
which equals one if the predicted abnormal returns are more negative than the median 
predicted returns, or zero otherwise for each security type. This dummy variable is 
employed to estimate the relation between expected costs and the sensitivity to internally 
generated funds. 

Table 22 presents results from a fixed effects regression model of loan growth, 
including the interaction between Large Abnormal Returns and additions to capital. 
Again, because of a potential simultaneity bias resulting from estimating costs, I 
instrument for this variable with a lagged observation of Large Abnormal Returns. As in 
the underwriting fee models, regardless of security type, banks that expect abnormal 
returns more negative than the median expected abnormal return are significantly more 
constrained by internally generated additions to capital. This suggests that expected 
abnormal stock returns influence the dependence on internally generated additions to 
capital, and that banks that anticipate larger external finance costs are more constrained by 
additions to capital than banks that anticipate smaller costs. Overall, these results provide 
evidence that investment-cashflow sensitivities proxy for the severity of information 
asymmetries. 



76 



Table 21 

Regression models relating abnormal stock returns to firm characteristics, correcting for 

selectivity bias using Heckman's two step procedure, (standard errors in parentheses). 





common 


stock 


preferred 


stock 


subordinated 


notes 


Variable 


Probit Model 
( 1 =issuer) 


Abnormal 
Return 


Probit Model 
( 1 =issuer) 


Abnormal 
Return 


Probit Model 
(l=issuer) 


Abnormal 
Return 


Bind 8 


0.46 ** 
(0.064) 


0.02* 
(0.008) 


0.05 
(0.145) 


-0.01 
(0.010) 


0.40 ** 
(0.140) 


-0.01 
(0.003) 


Log (Total Assets,.,) 


0.04* 
(0.019) 


0.002 
(0.003) 


0.40 ** 
(0.021) 


0.01 * 
(0.004) 


0.04* 
(0.019) 


0.002 * 
(0.001) 


Free Cash Flow / 
Loans t ., b 


0.23* 
(0.119) 


-0.03 
(0.019) 


-1.31 ** 
(0.116) 


0.03 
(0.023) 


0.15 
(0.123) 


0.02 ** 
(0.006) 


Lag (Additions to 
Capital / Loans,.,) 


-17.5** 
(2.089) 


-0.02 
(0.440) 


-8.72 ** 
(2.273) 


-0.17 
(0.358) 


4.69* 
(2.117) 


0.25* 
(0.129) 


Securities / Assets,., 


-5.73 ** 
(0.316) 


0.001 
(0.072) 


-3.44 ** 
(0.345) 


-0.01 
(0.070) 


-1.85** 
(0.305) 


0.03* 
(0.013) 


Target' 


18.7** 
(1.858) 


-0.25 
(0.362) 


19.8** 
(2.169) 


-0.02 
(0.373) 


6.53 ** 
(1.862) 


0.04 
(0.109) 


Risk d 


-27.31 ** 
(2.112) 


-0.48 
(0.884) 


-5.23 ** 
(2.026) 


0.86 
(0.819) 


-13.1 ** 
(2.121) 


-1.48* 
(0.628) 


3 month avg Stock 
Price / 36 month avg 


3.82 ** 
(0.531) 




7.60 ** 
(0.288) 




-5.48 ** 
(0.703) 




3 month avg Market 
Price / 36 mo avg 


30.8** 
(2.057) 




18.6** 
(2.267) 




15.0** 
(2.075) 




Hot 


0.13* 
(0.057) 




-0.32 ** 
(0.061) 




-0.12* 
(0.058) 




Issued in the Previous 
Year=l if yes, if no. 


-0.41 ** 
(0.102) 




-0.37 ** 
(0.118) 




-0.33 ** 
(0.077) 




Inverse Mills Ratio 
from Probit* 




0.01 

(0.018) 




0.02 
(0.012) 




-0.02 ** 
(0.001) 



a. Bind =1 if surplus capital is less than or equal to zero, =0 otherwise 

b. Free Cash Flow= net income less dividends and investment. 

c. Target = the bank's average surplus capital over the entire sample period minus it's actual surplus capital. 

d. Risk= standard deviation of daily stock return 

e. Inverse Mills Ratio = the probability of issuance derived from the Probit model 
*, ** denote significance at the 5% and 1% levels, respectively 



77 



Table 22 

Fixed effects regressions relating loan growth to internal additions to capital, expected 

abnormal stock returns, and firm financial characteristics. The sample consists of 289 

bank holding companies from 1982-1994 (standard errors in parentheses). 



Dependent Variable = (Loans, - 


Loans,., ) /Loans,., 










Variable 


common 


stock 


preferred 


stock 


subord. 


notes 


Additions to Capital / Loans,., 


4.52 ** 
(0.242) 


3.77 ** 
(0.207) 


4.51 ** 
(0.233) 


3.66** 
(0.204) 


4.68 ** 
(0.227) 


3.76** 
(0.199) 


Large Abnormal Returns,., * 
Additions to Capital / Loans,., a 


0.32* 
(0.177) 


0.37* 
(0.178) 


0.85 ** 
(0.210) 


0.84 ** 
(0.209) 


0.72 ** 
(0.189) 


0.76 ** 
(0.189) 


Surplus Capital / Assets,., 


0.80 ** 
(0.163) 




0.87 ** 
(0.155) 




0.95 ** 
(0.159) 




Surplus Capital *Additions to 
Capital / Loans,., 


-26.5 ** 
(4.722) 




-27.7 ** 
(4.458) 




-30.9 ** 
(4.551) 




Bind" 




-0.05 ** 
(0.009) 




-0.06 ** 
(0.009) 




-0.06 ** 
(0.009) 


Bind * Additions to Capital / 
Loans,., 




0.21 
(0.533) 




1.02* 
(0.511) 




0.97* 
(0.501) 


Securities / Assets,., 


0.12** 
(0.039) 


0.12** 
(0.039) 


0.13 ** 
(0.039) 


0.13** 
(0.038) 


0.11 ** 
(0.040) 


0.11 ** 
(0.040) 


Market / Book Assets,., 


0.26 ** 
(0.047) 


0.25 ** 
(0.048) 


0.26 ** 
(0.049) 


0.24 ** 
(0.049) 


0.24 ** 
(0.049) 


0.22 ** 
(0.049) 


log (Assets,.,) 


-0.07 ** 
(0.005) 


-0.07 ** 
(0.005) 


-0.06 ** 
(0.005) 


-0.07 ** 
(0.005) 


-0.07 ** 
(0.005) 


-0.07 ** 
(0.005) 


Lag loan growth 


0.07 ** 
(0.009) 


0.07 ** 
(0.009) 


0.08 ** 
(0.009) 


0.08 ** 
(0.009) 


0.06 ** 
(0.010) 


0.06 ** 
(0.010) 


R 2 


0.355 


0.351 


0.385 


0.384 


0.383 


0.379 


N (categories) 


1968 
(289) 


1968 
(289) 


1968 
(289) 


1968 
(289) 


1968 
(289) 


1968 
(289) 


F statistic, Bank dummies 


2.35** 


2.62** 


2.34** 


2.63** 


2.36** 


2.63 ** 



a. Large Abnormal Returns =1 if the firms predicted abnormal stock returns from the Abnormal Stock Returns 
model in Table 21 (corrected for selectivity bias) are more negative than the median predicted abnormal return, 
=0 otherwise. 

b. Bind=l if surplus capital<=0, otherwise. 

*, ** denote significance at the 5% and 1% levels, respectively 



CHAPTER 7 
SUMMARY AND CONCLUSIONS 

Overall, my results suggest that asymmetric information problems increase the 
costs of external finance for banking firms. In particular, I find a positive and significant 
relation between bank loan growth and internally generated additions to capital. 
Moreover, consistent with the hypothesis that capital requirements limit bank financing 
alternatives, this cashflow sensitivity of investment is positively related to the extent that 
capital requirements are binding. This relationship implies that increases in capital 
standards, which increase the likelihood that capital requirements are binding, could 
induce a slowdown in loan growth. 

I also find that the formulation of the capital ratio itself is important in determining 
bank loan growth. Specifically, with regulators enforcing leverage-based capital 
standards, banks can rely on a buffer stock of securities to fund investment in a liquidity 
crisis. This results in a negative relation between the cashflow sensitivity of investment 
and securities holdings. However, the use of risk-based standards substantially reduces 
the effectiveness of securities as financial slack. As a result, the change from leverage- 
based to risk-based standards may have caused banks to desire more surplus capital, and 
therefore may have had a negative impact on loan growth. 

My results also suggest that bank holding companies allocate capital in a way 
consistent with the operation of an internal capital market by holding companies that find 

78 



79 
equity expensive to raise externally. Specifically, I find that investment by bank 
subsidiaries is more sensitive to the cash flows and capitalization of its holding company 
than its own cash flows and capitalization. I also find that subsidiary investment is 
significantly related to the non-bank earnings of its holding company. These results are 
consistent with the hypothesis of costly external finance, and suggest that empirical studies 
of the effects of changes in capital requirements should be considered on the holding 
company level and not the individual bank level. 

Finally, I find that the severity of information asymmetries affects both the 
likelihood and the costs of an external capital issuance. In particular, I find a negative 
relation between the cash flow sensitivity of investment and the probability that banks 
issue external capital. I also find that firms which anticipate underwriting fees larger than 
the median expected fee for an external capital issuance exhibit significantly higher cash 
flow sensitivities of investment. Moreover, banks expecting abnormal stock returns more 
negative than the median expected abnormal return following the announcement of an 
external capital issue are significantly more constrained by internally generated funds. 
These results provide evidence that investment-cashflow sensitivities proxy for the severity 
of capital market imperfections. 



APPENDIX 
ESTIMATION OF RISK-WEIGHTED ASSETS 



A data set with complete risk-weighted assets data is available to me for 98 bank 
holding companies on December 31, 1995. 1 These data disaggregate total risk- weighted 
assets into three major categories: balance sheet assets, loan commitments, and 
derivatives. Table 23 presents descriptive statistics. The sample contains both very large 
and small banks, as total assets range from a low of $105 million to Citicorp's $216 
billion. In addition, risk- weighted assets range from $5 1 million to $230 billion. By far, 
balance sheet assets contribute the most to risk-weighted assets. For many banks, mostly 
small ones, off-balance sheet assets hardly add to risk-weighted assets at all. Therefore, 
for the most accurate approximation of total risk- weighted assets, I estimate each major 
component separately. That is, I decompose risk-weighted assets into its three broad 
categories. A regression for each component is specified, and parameter estimates 
obtained. The regressions are specified as follows: 

RWBS = ttjLOANS + a 2 SECS 
RWLC = PjSLC + P 2 LC + P 2 LOC 

RWD = Y 1 FEXPimCH+Y 2 FEXPOPT+Y 3 FEXWOPT+Y 4 FEXS\\T+Y 5 FUTURES 
+Y 6 WOPT +Y7POPT +y 8 SWAPS 



1 Data set supplied by Carolyn Takeda. Before December 1991, the breakdown of 
risk-weighted assets into its components is not available. 



80 



81 



Table 23 

Descriptive Statistics of 98 bank holding companies at year-end 1991. Data were 

collected from the Federal Reserve Y-9 Data Tapes. This sample consists of banks for 

which complete risk-based capital data was available. * 



Variable 


Mean 


Median 


Min 


Max 


Total Assets (millions) 


17,474 


5,317 


105 


216,920 


Risk- Weighted Assets (millions) 


14,700 


3,787 


51 


238,000 


Risk- Weighted Assets, from on- 
balance sheet items (millions) 


9,738 


2,229 


18 


165,000 


Risk- Weighted Assets, from loan 
commitments (millions) 


2,435 


216 


20 


54,800 


Risk- Weighted Assets, from derivative 
assets (millions) 


424 








108,000 


Loans / TA 


0.6008 


0.6358 


0.1266 


0.8057 


Securities / TA 


0.2399 


0.2233 


0.0348 


0.6152 


(Loans, - Loans,.,) / Loans,., 


0.0054 


-0.0044 


-0.3558 


0.3206 


Internal Additions to Capital / Loans,., 


0.0096 


0.0120 


-0.0213 


0.0219 


Market / Book Assets 


1.0182 


1.0149 


0.9554 


1.2055 


Book Capital in Excess of Requirement 
/ Assets 


0.0228 


0.0226 


-0.0072 


0.2046 



* Special thanks to Carolyn Takeda for use of this data set. 



82 

RWBS = risk- weighted assets attributable to the balance sheet 

LOANS = loans outstanding 

SECS = securities held 

RWLC = risk- weighted assets attributable to loan commitments 

SLC = stand-by letters of credit 

LC = loan commitments 

LOC = lines of credit 

RWD = risk-weighted assets attributable to derivative assets 

FEXPURCH = foreign exchange purchase commitments 

FEXPOPT = foreign exchange purchase options 

FEXWOPT = foreign exchange written options 

FEXSWP = foreign exchange swaps 

FUTURES ■ futures and forwards 

WOPT = written options 

POPT = purchase options 

SWAPS = non-foreign exchange swaps. 

Actual risk-based capital data are used as the dependent variables, and broad 
classifications of on and off-balance sheet components are used as the independent 
variables. Coefficient estimates from these equations are then used to approximate the 
risk-weights assigned to each component for purposes of computing total risk- weighted 
assets. Consequently, this procedure approximates risk-based capital ratios for all banks 
from 1990 to present. 2 

Table 24 presents the regression results. As expected, the coefficient on loans is 
very significant and close to unity. Moreover, the results estimate the risk-weight on 
stand-by letters of credit to be approximately one. 3 The next largest risk-weight comes 
from securities, at 0.34. No variable has a coefficient significantly greater than one, which 
is consistent with risk-based capital standards. 



2 Reporting requirements from 1990 to present ensure sufficient off-balance sheet 
data to estimate risk-weighted assets for the majority of firms in the sample. 

Coefficient not significantly different from one. 



83 

Table 24 

Least squares estimation of risk-weighted assets (RWA). Data were collected from the 

Federal Reserve Y-9 Data Tapes. A sample of 98 firms contains complete RWA data for 

year-end 1991. These observations are used to estimate components of RWA. RWA is 

decomposed into three categories, balance sheet assets, off-balance sheet loan 

commitments, and derivative sheet assets. Regressions use the actual amount of RWA 

attributable to a category as the dependent variable. Broad classes of asset items are used 

as independent variables. Regressions are performed using White's correction for 

heteroskedasticity. Standard errors are in parenthesis. 



Variable 


RWA: Balance 
Sheet Assets 


RWA: Loan 
Commitments 


RWA: Derivative 
Assets 


Loans 


*** 1.0197 
(0.0403) 






Securities 


0.3393 
(0.2396) 






Stand-by Letters of 
Credit 




*** 1.3174 
(0.3134) 




Loan Commitments 




*** 0.1483 
(0.0424) 




Lines of Credit 




-0.5543 
(1.5209) 




Foreign Exchange (FEX) 
Purchase Comm. 






*** 0.0069 
(0.0008) 


Foreign Exchange 
Purchase Options 






*** 0.3266 
(0.0528) 


Foreign Exchange 
Written Options 






*** -0.2819 
(0.0482) 


Foreign Exchange Swaps 






*** 0.0435 
(0.0012) 


Futures and Forwards 






*** -0.0069 
(0.0006) 


Written Options (non 
FEX) 






-0.0039 
(0.0075) 


Purchase Options (non 
FEX) 






*** 0.0201 
(0.0058) 


SWAPS (non FEX) 






*** 0.0134 
(0.0001) 


N 

Adjusted R Squared 


98 

0.9940 


98 

0.9793 


98 
0.9999 



* ** *** 



denote significant at the 10%, 5%, and 1% levels respectively. 



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86 



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BIOGRAPHICAL SKETCH 
David Frederic Marcus was born the third child of Jeffery Neal and Ellen Janet 
Marcus on September 4, 1968, in Eau Claire, Wisconsin. He attended the University of 
Colorado at Boulder from 1986-1990. David graduated Magna Cum Laude with a 
Bachelor of Science. Following graduation, David worked for two years before enrolling 
at the University of Florida as a doctoral student. 



87 



I certify that I have read this study and that in my opinion it conforms to acceptable 
standards of scholarly presentation and is fully adequate, in scope and quality, as a dissertation for 
the degree of Doctor of Philosophy. /s 



iristophej<£ef'james, Chairman 
SunBank^Professor of Finance, 
Insurance, and Real Estate 

I certify that I have read this study and that in my opinion it conforms to acceptable 
standards of scholarly presentation and is fully adequate, in scope and quality, as a dissertation for 
the degree of Doctor of Philosophy. 




7 /SLa 



Dr. Joel F. Houston 
Associate Professor of Finance 
Insurance, and Real Estate 



I certify that I have read this study and that in my opinion it conforms to acceptable 
standards of scholarly presentation and is fully adequate, in scope and quality, as a dissertation for 
the degree of Doctor of Philosophy. 



Dr. Michael D. Ryngaert 
Associate Professor of Finance 
Insurance, and Real Estate 



I certify that I have read this study and that in my opinion it conforms to acceptable 
standards of scholarly presentation and is fully adequate, in scope and quality, as a dissertation for 
the degree of Doctor of Philosophy. 




Jonathan H. Hamilton 
Associate Professor of Economics 

This dissertation was submitted to the Graduate Faculty of the Department of Finance, 
Insurance, and Real Estate in the College of Business Administration and to the Graduate School 
and was accepted as partial fulfillment of the requirements for the degree of Doctor of 
Philosophy. 



August, 1996 Dean, Graduate School 



LD 

1780 

199^ 



UNIVERSITY OF FLORIDA 



3 1262 08555 0852